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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
jonatasgrosman/exp_w2v2t_it_vp-100k_s449
|
76cbb34cfc7aa892c277c37ccdbcee79ebce52b5
|
2022-07-08T19:01:30.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-100k_s449
| 2 | null |
transformers
| 26,700 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-100k_s449
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
huggingtweets/_anushkasharmaa
|
84afd581cc7f37d41d37565201c4229ccd75df93
|
2022-07-08T19:04:13.000Z
|
[
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] |
text-generation
| false |
huggingtweets
| null |
huggingtweets/_anushkasharmaa
| 2 | null |
transformers
| 26,701 |
---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1544699011642171392/mEzKAPWL_400x400.jpg')">
</div>
<div
style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('')">
</div>
<div
style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('')">
</div>
</div>
<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div>
<div style="text-align: center; font-size: 16px; font-weight: 800">Anushka Sharma</div>
<div style="text-align: center; font-size: 14px;">@_anushkasharmaa</div>
</div>
I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)!
## How does it work?
The model uses the following pipeline.
To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI).
## Training data
The model was trained on tweets from Anushka Sharma.
| Data | Anushka Sharma |
| --- | --- |
| Tweets downloaded | 431 |
| Retweets | 129 |
| Short tweets | 80 |
| Tweets kept | 222 |
[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1z7v8rf0/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
## Training procedure
The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @_anushkasharmaa's tweets.
Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1qxdz9eg) for full transparency and reproducibility.
At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1qxdz9eg/artifacts) is logged and versioned.
## How to use
You can use this model directly with a pipeline for text generation:
```python
from transformers import pipeline
generator = pipeline('text-generation',
model='huggingtweets/_anushkasharmaa')
generator("My dream is", num_return_sequences=5)
```
## Limitations and bias
The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
In addition, the data present in the user's tweets further affects the text generated by the model.
## About
*Built by Boris Dayma*
[](https://twitter.com/intent/follow?screen_name=borisdayma)
For more details, visit the project repository.
[](https://github.com/borisdayma/huggingtweets)
|
jonatasgrosman/exp_w2v2t_it_vp-100k_s358
|
55e10b052935bab77f3e4d376b0273f7960c5b5c
|
2022-07-08T19:05:46.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-100k_s358
| 2 | null |
transformers
| 26,702 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-100k_s358
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_xlsr-53_s387
|
595d707de8e476caec5caa97a5c22903868a6f28
|
2022-07-08T19:09:45.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_xlsr-53_s387
| 2 | null |
transformers
| 26,703 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_xlsr-53_s387
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_xlsr-53_s237
|
ed0affa2a883d78401eaef1c4a61de3acfa5b7b3
|
2022-07-08T19:12:58.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_xlsr-53_s237
| 2 | null |
transformers
| 26,704 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_xlsr-53_s237
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_xlsr-53_s79
|
1de453033bdcab0db8c9a144d6a245e8c8e6361e
|
2022-07-08T19:16:35.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_xlsr-53_s79
| 2 | null |
transformers
| 26,705 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_xlsr-53_s79
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_unispeech_s714
|
bc88e58780d56bc4e31ffcb97bcedf35e5fcce50
|
2022-07-08T19:20:02.000Z
|
[
"pytorch",
"unispeech",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_unispeech_s714
| 2 | null |
transformers
| 26,706 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_unispeech_s714
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_unispeech_s626
|
579ef119ba31b5a8a93767e13d974c2cc37c4fff
|
2022-07-08T19:23:51.000Z
|
[
"pytorch",
"unispeech",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_unispeech_s626
| 2 | null |
transformers
| 26,707 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_unispeech_s626
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_unispeech_s156
|
c52675968f981a3fc866899f9d837768d848e5c5
|
2022-07-08T19:27:36.000Z
|
[
"pytorch",
"unispeech",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_unispeech_s156
| 2 | null |
transformers
| 26,708 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_unispeech_s156
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_hubert_s722
|
d71779504448205087aa46f365411ea1ddcc4bd5
|
2022-07-08T19:30:54.000Z
|
[
"pytorch",
"hubert",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_hubert_s722
| 2 | null |
transformers
| 26,709 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_hubert_s722
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_hubert_s21
|
b3c4c4cc3f62182cc91644edae5b5b94e621e86e
|
2022-07-08T19:37:22.000Z
|
[
"pytorch",
"hubert",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_hubert_s21
| 2 | null |
transformers
| 26,710 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_hubert_s21
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_hubert_s474
|
a198274e60fddc1a228b27e51debb6369156de3e
|
2022-07-08T19:40:35.000Z
|
[
"pytorch",
"hubert",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_hubert_s474
| 2 | null |
transformers
| 26,711 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_hubert_s474
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-sv_s791
|
e2a61ecadac3f7cb3238cb91d9569e10539502a9
|
2022-07-08T19:44:09.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-sv_s791
| 2 | null |
transformers
| 26,712 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-sv_s791
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-sv_s149
|
422551a341c41597998632d38c21801896a22759
|
2022-07-08T19:47:29.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-sv_s149
| 2 | null |
transformers
| 26,713 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-sv_s149
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-sv_s1
|
d6662142b3de03328160b43993b33487f8c6c068
|
2022-07-08T19:51:06.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-sv_s1
| 2 | null |
transformers
| 26,714 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-sv_s1
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_no-pretraining_s615
|
9ebb422a252e9aea7ed72b3469e76bf8d6e883fd
|
2022-07-08T19:55:28.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_no-pretraining_s615
| 2 | null |
transformers
| 26,715 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_no-pretraining_s615
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_no-pretraining_s842
|
8701b90611612fbc83d824aa501bd6aa0d888088
|
2022-07-08T19:58:51.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_no-pretraining_s842
| 2 | null |
transformers
| 26,716 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_no-pretraining_s842
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_no-pretraining_s764
|
262a8f1ec983235fe7906fb331188bc6efeebdbe
|
2022-07-08T20:02:47.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_no-pretraining_s764
| 2 | null |
transformers
| 26,717 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_no-pretraining_s764
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_wavlm_s895
|
4a6d513ec92fec4d167d574ea8868d246682bed8
|
2022-07-08T20:09:44.000Z
|
[
"pytorch",
"wavlm",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_wavlm_s895
| 2 | null |
transformers
| 26,718 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_wavlm_s895
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_wavlm_s25
|
41c9c6a3117ae856efae28b13ddf75d23ce50359
|
2022-07-08T20:13:30.000Z
|
[
"pytorch",
"wavlm",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_wavlm_s25
| 2 | null |
transformers
| 26,719 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_wavlm_s25
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s213
|
e37623a41c475aa1d3bd0fe1fa520b3776f75567
|
2022-07-08T20:16:37.000Z
|
[
"pytorch",
"unispeech",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s213
| 2 | null |
transformers
| 26,720 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_unispeech-ml_s213
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s246
|
4a357fb104ea9254065c8b668421e830dd78cee0
|
2022-07-08T20:20:05.000Z
|
[
"pytorch",
"unispeech",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s246
| 2 | null |
transformers
| 26,721 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_unispeech-ml_s246
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784
|
0ecc87b8dd6db754b70712b7b43aab0030062568
|
2022-07-08T20:23:31.000Z
|
[
"pytorch",
"unispeech",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_unispeech-ml_s784
| 2 | null |
transformers
| 26,722 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_unispeech-ml_s784
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-fr_s821
|
370856b51df145c3fc8174c70766fb6ed5554d16
|
2022-07-08T20:27:50.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-fr_s821
| 2 | null |
transformers
| 26,723 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-fr_s821
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-fr_s579
|
bc8c6fda9172202f8d2cc79f1545f264adcc7acf
|
2022-07-08T20:32:13.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-fr_s579
| 2 | null |
transformers
| 26,724 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-fr_s579
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-fr_s557
|
29128deecea0e8547dbe1dd48fb032b97ad2e4ea
|
2022-07-08T20:35:34.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-fr_s557
| 2 | null |
transformers
| 26,725 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-fr_s557
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-es_s33
|
56ab3820dc5e4cb61653d8eebdd5975520b955d4
|
2022-07-08T20:39:11.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-es_s33
| 2 | null |
transformers
| 26,726 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-es_s33
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-es_s496
|
db98f18235704a6c3f6f861af36987d1f11cf196
|
2022-07-08T20:42:33.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-es_s496
| 2 | null |
transformers
| 26,727 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-es_s496
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-es_s878
|
2d4abb127a6b8a6519c6f9f0e220adb8a1a3f006
|
2022-07-08T20:47:26.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-es_s878
| 2 | null |
transformers
| 26,728 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-es_s878
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
huggingtweets/redo
|
68672fd8f6f9b1b9b860e94473d01c081d36bb95
|
2022-07-08T21:02:22.000Z
|
[
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] |
text-generation
| false |
huggingtweets
| null |
huggingtweets/redo
| 2 | null |
transformers
| 26,729 |
---
language: en
thumbnail: http://www.huggingtweets.com/redo/1657314137996/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/809537557943881728/GU7lSXyY_400x400.jpg')">
</div>
<div
style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('')">
</div>
<div
style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('')">
</div>
</div>
<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div>
<div style="text-align: center; font-size: 16px; font-weight: 800">Gregory Renard</div>
<div style="text-align: center; font-size: 14px;">@redo</div>
</div>
I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)!
## How does it work?
The model uses the following pipeline.
To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI).
## Training data
The model was trained on tweets from Gregory Renard.
| Data | Gregory Renard |
| --- | --- |
| Tweets downloaded | 3243 |
| Retweets | 579 |
| Short tweets | 62 |
| Tweets kept | 2602 |
[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1hp88bd4/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
## Training procedure
The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @redo's tweets.
Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3ncfpyxs) for full transparency and reproducibility.
At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3ncfpyxs/artifacts) is logged and versioned.
## How to use
You can use this model directly with a pipeline for text generation:
```python
from transformers import pipeline
generator = pipeline('text-generation',
model='huggingtweets/redo')
generator("My dream is", num_return_sequences=5)
```
## Limitations and bias
The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
In addition, the data present in the user's tweets further affects the text generated by the model.
## About
*Built by Boris Dayma*
[](https://twitter.com/intent/follow?screen_name=borisdayma)
For more details, visit the project repository.
[](https://github.com/borisdayma/huggingtweets)
|
jonatasgrosman/exp_w2v2t_it_vp-nl_s27
|
0677593b3ef62b0b405af36e746fd59af0ea136f
|
2022-07-08T20:51:06.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-nl_s27
| 2 | null |
transformers
| 26,730 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-nl_s27
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-nl_s222
|
da53bcf94ee904e11a98965a6aaf55890561644e
|
2022-07-08T20:54:30.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-nl_s222
| 2 | null |
transformers
| 26,731 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-nl_s222
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-nl_s335
|
980e324a760e42ee231f02976960f40224529df7
|
2022-07-08T20:58:20.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-nl_s335
| 2 | null |
transformers
| 26,732 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-nl_s335
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s500
|
60afae3a1027380a8be50699307eadfa341ac386
|
2022-07-08T21:10:22.000Z
|
[
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s500
| 2 | null |
transformers
| 26,733 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_unispeech-sat_s500
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s306
|
7eb6122ea76c6130bb33c8dc2649372b4d63ea62
|
2022-07-08T21:48:04.000Z
|
[
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s306
| 2 | null |
transformers
| 26,734 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_unispeech-sat_s306
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s692
|
cfc5ff6c6e2c81056d398919afce7324d2e2dbed
|
2022-07-08T21:56:35.000Z
|
[
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_unispeech-sat_s692
| 2 | null |
transformers
| 26,735 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_unispeech-sat_s692
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_xls-r_s417
|
43b5d97a2e0f29a36bad5c30ed2196dce43722fb
|
2022-07-08T22:22:06.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_xls-r_s417
| 2 | null |
transformers
| 26,736 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_xls-r_s417
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_xls-r_s226
|
5eef06e6df547a55e4beb633c2d4bcfbc60c5888
|
2022-07-08T22:28:27.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_xls-r_s226
| 2 | null |
transformers
| 26,737 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_xls-r_s226
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_xls-r_s156
|
0de093bf53ff7829124a9a55a2819f9c2a190119
|
2022-07-08T22:33:51.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_xls-r_s156
| 2 | null |
transformers
| 26,738 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_xls-r_s156
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s317
|
8a0b587733d6bb9f2de8a72d3457123a56083326
|
2022-07-08T22:37:57.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s317
| 2 | null |
transformers
| 26,739 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_r-wav2vec2_s317
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s646
|
8cfd419f750d876786283e0a33c6dce2c4ed3497
|
2022-07-08T22:41:20.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s646
| 2 | null |
transformers
| 26,740 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_r-wav2vec2_s646
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s578
|
160b7d385a4ca4a42c1da9171fae1f88330d0feb
|
2022-07-08T22:44:54.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_r-wav2vec2_s578
| 2 | null |
transformers
| 26,741 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_r-wav2vec2_s578
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-it_s324
|
a775b71cfc3db0596d7b2430398e82a6f74ff65c
|
2022-07-08T22:48:14.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-it_s324
| 2 | null |
transformers
| 26,742 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-it_s324
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-it_s411
|
7bb0a26dfc637b02ccfbb03b7086e035f669b771
|
2022-07-08T22:51:42.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-it_s411
| 2 | null |
transformers
| 26,743 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-it_s411
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_it_vp-it_s965
|
ab60c0b44b0342ce6a0609ef3b1d11f64c328306
|
2022-07-08T22:55:05.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_it_vp-it_s965
| 2 | null |
transformers
| 26,744 |
---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- it
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_it_vp-it_s965
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_vp-fr_s438
|
0048d545718140690d6aad311a8dd5ab52335b49
|
2022-07-09T01:03:57.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_vp-fr_s438
| 2 | null |
transformers
| 26,745 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_vp-fr_s438
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_vp-fr_s179
|
a547076c0cf09a0a6c01ed16c57aaf85fb6d1f59
|
2022-07-09T01:07:16.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_vp-fr_s179
| 2 | null |
transformers
| 26,746 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_vp-fr_s179
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_vp-es_s169
|
3a865415343bc81da8d1860abe6f59b965b70d5a
|
2022-07-09T01:10:31.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_vp-es_s169
| 2 | null |
transformers
| 26,747 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_vp-es_s169
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_vp-es_s281
|
c919aa13ca7b533bfc2ed4a83fa2c59596238745
|
2022-07-09T01:13:47.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_vp-es_s281
| 2 | null |
transformers
| 26,748 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_vp-es_s281
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_vp-es_s980
|
b6a692fe04646dcce0a19ec10046125f4e04f5cc
|
2022-07-09T01:17:07.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_vp-es_s980
| 2 | null |
transformers
| 26,749 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_vp-es_s980
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_vp-nl_s863
|
cf228355e61a87cfe8ca1e86403d7b60690368a2
|
2022-07-09T01:20:23.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_vp-nl_s863
| 2 | null |
transformers
| 26,750 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_vp-nl_s863
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_vp-nl_s93
|
c540aabd184130c7126eb1b3b1ea716e9b7d9013
|
2022-07-09T01:23:53.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_vp-nl_s93
| 2 | null |
transformers
| 26,751 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_vp-nl_s93
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_vp-nl_s44
|
900ab7b0e6d62908fd2c022d10516dfb062c5370
|
2022-07-09T01:27:14.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_vp-nl_s44
| 2 | null |
transformers
| 26,752 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_vp-nl_s44
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_unispeech-sat_s655
|
d876baeb3923982188036c036cf5d22bf4acbce7
|
2022-07-09T01:30:33.000Z
|
[
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_unispeech-sat_s655
| 2 | null |
transformers
| 26,753 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_unispeech-sat_s655
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_unispeech-sat_s115
|
90066e0f759e213769cc7ae52b1b0dc26bd3153f
|
2022-07-09T01:33:39.000Z
|
[
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_unispeech-sat_s115
| 2 | null |
transformers
| 26,754 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_unispeech-sat_s115
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_unispeech-sat_s26
|
7bf7b1d986b9d3ba7d3e1f406306f0d15d85f70d
|
2022-07-09T01:36:57.000Z
|
[
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_unispeech-sat_s26
| 2 | null |
transformers
| 26,755 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_unispeech-sat_s26
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_xls-r_s515
|
bd11242f1b4fcb0f3f28b1f61959776a325d3811
|
2022-07-09T01:40:22.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_xls-r_s515
| 2 | null |
transformers
| 26,756 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_xls-r_s515
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_xls-r_s250
|
fced91821a14eebe0b7fe9609407f95e5b2ed74c
|
2022-07-09T01:43:44.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_xls-r_s250
| 2 | null |
transformers
| 26,757 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_xls-r_s250
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_xls-r_s859
|
529abcccb31b327648bf6197898fdd1d634b6dcf
|
2022-07-09T01:47:09.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_xls-r_s859
| 2 | null |
transformers
| 26,758 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_xls-r_s859
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_r-wav2vec2_s456
|
7c0c0f41b3d562a59fda81b9f71a0687a3435518
|
2022-07-09T01:50:41.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_r-wav2vec2_s456
| 2 | null |
transformers
| 26,759 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_r-wav2vec2_s456
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_r-wav2vec2_s251
|
a277c4ac5e3e1e2511caace77e52189f6b2ac34e
|
2022-07-09T01:54:18.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_r-wav2vec2_s251
| 2 | null |
transformers
| 26,760 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_r-wav2vec2_s251
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_r-wav2vec2_s459
|
773d1d99f2ab1d4eb1de8657441a94dfb750b4b1
|
2022-07-09T01:57:35.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_r-wav2vec2_s459
| 2 | null |
transformers
| 26,761 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_r-wav2vec2_s459
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_vp-it_s878
|
38426a406538d2c31350ebfc65e77d54223f5cb1
|
2022-07-09T02:00:45.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_vp-it_s878
| 2 | null |
transformers
| 26,762 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_vp-it_s878
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_fr_vp-it_s203
|
de7be11480c495ec59a1b91ae0d48ce914d3bf99
|
2022-07-09T02:04:23.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_fr_vp-it_s203
| 2 | null |
transformers
| 26,763 |
---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_fr_vp-it_s203
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (fr)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
okite97/xlm-roberta-base-finetune-panx-de
|
a7695d9511ca28b37f5d680c2320c352b788bcd0
|
2022-07-09T02:30:05.000Z
|
[
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"dataset:xtreme",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
okite97
| null |
okite97/xlm-roberta-base-finetune-panx-de
| 2 | null |
transformers
| 26,764 |
---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetune-panx-de
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.de
metrics:
- name: F1
type: f1
value: 0.8611443210930829
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetune-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1405
- F1: 0.8611
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2542 | 1.0 | 787 | 0.1788 | 0.8083 |
| 0.1307 | 2.0 | 1574 | 0.1371 | 0.8488 |
| 0.0784 | 3.0 | 2361 | 0.1405 | 0.8611 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|
okite97/xlm-roberta-base-finetuned-panx-de-fr
|
97ed8a35613950bd68c02dad316e4ed5409ae627
|
2022-07-09T03:10:18.000Z
|
[
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
okite97
| null |
okite97/xlm-roberta-base-finetuned-panx-de-fr
| 2 | null |
transformers
| 26,765 |
---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de-fr
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de-fr
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1196
- F1: 0.8973
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2837 | 1.0 | 1073 | 0.1775 | 0.8379 |
| 0.1446 | 2.0 | 2146 | 0.1301 | 0.8767 |
| 0.0917 | 3.0 | 3219 | 0.1196 | 0.8973 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|
okite97/xlm-roberta-base-finetuned-panx-fr
|
90d496532f89dcb35ba71589e18e08b6e3e825b1
|
2022-07-09T03:29:41.000Z
|
[
"pytorch",
"xlm-roberta",
"token-classification",
"dataset:xtreme",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
okite97
| null |
okite97/xlm-roberta-base-finetuned-panx-fr
| 2 | null |
transformers
| 26,766 |
---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-fr
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.fr
metrics:
- name: F1
type: f1
value: 0.809109176155392
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-fr
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3390
- F1: 0.8091
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6995 | 1.0 | 144 | 0.3922 | 0.7317 |
| 0.3222 | 2.0 | 288 | 0.3372 | 0.7958 |
| 0.208 | 3.0 | 432 | 0.3390 | 0.8091 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|
okite97/xlm-roberta-base-finetuned-panx-it
|
26cc6a3a53b2bb10ae025a67b4cb330fdc5bf311
|
2022-07-09T03:46:31.000Z
|
[
"pytorch",
"xlm-roberta",
"token-classification",
"dataset:xtreme",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
okite97
| null |
okite97/xlm-roberta-base-finetuned-panx-it
| 2 | null |
transformers
| 26,767 |
---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-it
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.it
metrics:
- name: F1
type: f1
value: 0.8289473684210525
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-it
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2403
- F1: 0.8289
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.668 | 1.0 | 105 | 0.2886 | 0.7818 |
| 0.2583 | 2.0 | 210 | 0.2421 | 0.8202 |
| 0.1682 | 3.0 | 315 | 0.2403 | 0.8289 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|
okite97/xlm-roberta-base-finetuned-panx-en
|
d5d6b64d6d89b091e42f46e21dbe11c54ecfb7fc
|
2022-07-09T04:03:37.000Z
|
[
"pytorch",
"xlm-roberta",
"token-classification",
"dataset:xtreme",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
okite97
| null |
okite97/xlm-roberta-base-finetuned-panx-en
| 2 | null |
transformers
| 26,768 |
---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-en
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.en
metrics:
- name: F1
type: f1
value: 0.6994475138121546
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-en
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3848
- F1: 0.6994
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.0435 | 1.0 | 74 | 0.5169 | 0.5532 |
| 0.4719 | 2.0 | 148 | 0.4224 | 0.6630 |
| 0.3424 | 3.0 | 222 | 0.3848 | 0.6994 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|
okite97/xlm-roberta-base-finetuned-panx-all
|
1bc0865670bfc6e641b6682aa47cdb621d0dd620
|
2022-07-09T04:33:41.000Z
|
[
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
okite97
| null |
okite97/xlm-roberta-base-finetuned-panx-all
| 2 | null |
transformers
| 26,769 |
---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-all
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-all
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1883
- F1: 0.8538
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2967 | 1.0 | 1109 | 0.2050 | 0.8180 |
| 0.1571 | 2.0 | 2218 | 0.1880 | 0.8415 |
| 0.0983 | 3.0 | 3327 | 0.1883 | 0.8538 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s451
|
576c41e8f8ae6316a410b174b05cb841d857b87e
|
2022-07-09T13:41:24.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s451
| 2 | null |
transformers
| 26,770 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_wav2vec2_s451
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s818
|
c7dc11e00a14e3e5c8c02591b95de40665645401
|
2022-07-09T14:06:26.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s818
| 2 | null |
transformers
| 26,771 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_wav2vec2_s818
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s732
|
985447570c91ffdc99bc5cd2e9b7eb077689fac5
|
2022-07-09T14:33:48.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_wav2vec2_s732
| 2 | null |
transformers
| 26,772 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_wav2vec2_s732
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s108
|
983eee09088e95fa68b03061cc67762c8b502959
|
2022-07-09T15:01:41.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s108
| 2 | null |
transformers
| 26,773 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_vp-100k_s108
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s904
|
cb264fb4b8d5062d50a30d3c574c47c7d53f7425
|
2022-07-09T15:16:59.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s904
| 2 | null |
transformers
| 26,774 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_vp-100k_s904
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
huangjia/xlm-roberta-base-finetuned-panx-de
|
f69700072620892b96db3675aaf52f0f4eb1a0ed
|
2022-07-09T15:39:43.000Z
|
[
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"dataset:xtreme",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
huangjia
| null |
huangjia/xlm-roberta-base-finetuned-panx-de
| 2 | null |
transformers
| 26,775 |
---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.de
metrics:
- name: F1
type: f1
value: 0.8550872422388397
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1333
- F1: 0.8551
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 263 | 0.1573 | 0.8137 |
| 0.2142 | 2.0 | 526 | 0.1386 | 0.8466 |
| 0.2142 | 3.0 | 789 | 0.1333 | 0.8551 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.2
- Datasets 1.18.4
- Tokenizers 0.10.3
|
huangjia/xlm-roberta-base-finetuned-panx-de-fr
|
db938cf5a89b647be1ca3ee6ebfe1f4c88b7f24c
|
2022-07-09T15:58:43.000Z
|
[
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
huangjia
| null |
huangjia/xlm-roberta-base-finetuned-panx-de-fr
| 2 | null |
transformers
| 26,776 |
---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de-fr
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de-fr
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1584
- F1: 0.8537
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 358 | 0.1776 | 0.8263 |
| 0.2394 | 2.0 | 716 | 0.1599 | 0.8447 |
| 0.2394 | 3.0 | 1074 | 0.1584 | 0.8537 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.2
- Datasets 1.18.4
- Tokenizers 0.10.3
|
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s847
|
6bc2933e3372fb5f4fbd578b7af9ff380cc83b83
|
2022-07-09T15:48:44.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_vp-100k_s847
| 2 | null |
transformers
| 26,777 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_vp-100k_s847
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s328
|
4d5c85d839f55c101857ab2cbf4aaf5fb3e7e974
|
2022-07-09T15:52:26.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s328
| 2 | null |
transformers
| 26,778 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_xlsr-53_s328
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s131
|
5b200e7d5046022fcc7ae3773b39deb562a9c8d0
|
2022-07-09T15:56:30.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s131
| 2 | null |
transformers
| 26,779 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_xlsr-53_s131
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s624
|
9ee84e5ec4459b37743b2a578dbb5af4e635f725
|
2022-07-09T16:00:26.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_xlsr-53_s624
| 2 | null |
transformers
| 26,780 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_xlsr-53_s624
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
huangjia/xlm-roberta-base-finetuned-panx-fr
|
93a814a2fe4f97af3c595cf44173629ca64bb039
|
2022-07-09T16:05:20.000Z
|
[
"pytorch",
"xlm-roberta",
"token-classification",
"dataset:xtreme",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
huangjia
| null |
huangjia/xlm-roberta-base-finetuned-panx-fr
| 2 | null |
transformers
| 26,781 |
---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-fr
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.fr
metrics:
- name: F1
type: f1
value: 0.8204272363150867
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-fr
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2739
- F1: 0.8204
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 96 | 0.3708 | 0.7672 |
| 0.506 | 2.0 | 192 | 0.2967 | 0.8130 |
| 0.506 | 3.0 | 288 | 0.2739 | 0.8204 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.2
- Datasets 1.18.4
- Tokenizers 0.10.3
|
huangjia/xlm-roberta-base-finetuned-panx-it
|
4b35a8a06e5b05efa9e29f18125689f1d34b88d4
|
2022-07-09T16:09:16.000Z
|
[
"pytorch",
"xlm-roberta",
"token-classification",
"dataset:xtreme",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
huangjia
| null |
huangjia/xlm-roberta-base-finetuned-panx-it
| 2 | null |
transformers
| 26,782 |
---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-it
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.it
metrics:
- name: F1
type: f1
value: 0.7938060309698453
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-it
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2687
- F1: 0.7938
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 35 | 0.4625 | 0.6674 |
| 0.7337 | 2.0 | 70 | 0.3035 | 0.7613 |
| 0.7337 | 3.0 | 105 | 0.2687 | 0.7938 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.2
- Datasets 1.18.4
- Tokenizers 0.10.3
|
huangjia/xlm-roberta-base-finetuned-panx-all
|
19cfa84d0da22407b2d9b7ae0bbb3aef52547aa6
|
2022-07-09T16:25:28.000Z
|
[
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] |
token-classification
| false |
huangjia
| null |
huangjia/xlm-roberta-base-finetuned-panx-all
| 2 | null |
transformers
| 26,783 |
---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-all
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-all
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1709
- F1: 0.8561
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 418 | 0.2042 | 0.8064 |
| 0.2421 | 2.0 | 836 | 0.1773 | 0.8376 |
| 0.2421 | 3.0 | 1254 | 0.1709 | 0.8561 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.10.2
- Datasets 1.18.4
- Tokenizers 0.10.3
|
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s149
|
cca43c32031d3248c3c4ecc5f509295a889b95c3
|
2022-07-09T16:18:55.000Z
|
[
"pytorch",
"unispeech",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s149
| 2 | null |
transformers
| 26,784 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_unispeech_s149
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s449
|
d7d4a0f5f47abd4fd77b5a551f98ab941f580724
|
2022-07-09T16:30:10.000Z
|
[
"pytorch",
"unispeech",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s449
| 2 | null |
transformers
| 26,785 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_unispeech_s449
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s358
|
d7327ba3ca79551f26d80203a11dac096c1ad0fe
|
2022-07-09T16:37:28.000Z
|
[
"pytorch",
"unispeech",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_unispeech_s358
| 2 | null |
transformers
| 26,786 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_unispeech_s358
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_hubert_s805
|
f5ffae54ba92d6a565d6027ef855b8dd85c161db
|
2022-07-09T16:45:49.000Z
|
[
"pytorch",
"hubert",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_hubert_s805
| 2 | null |
transformers
| 26,787 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_hubert_s805
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_hubert_s730
|
9c14b96f8db661000edd496a29b8e86f45942ad1
|
2022-07-09T16:53:37.000Z
|
[
"pytorch",
"hubert",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_hubert_s730
| 2 | null |
transformers
| 26,788 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_hubert_s730
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_hubert_s930
|
beaa1908ecf26a40afcaffdf877bd4fcfd1b90ca
|
2022-07-09T16:58:31.000Z
|
[
"pytorch",
"hubert",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_hubert_s930
| 2 | null |
transformers
| 26,789 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_hubert_s930
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s363
|
0c2a76da879be965e2dcdf98a0cdd5e5a5b2f12e
|
2022-07-09T17:05:30.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s363
| 2 | null |
transformers
| 26,790 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_vp-sv_s363
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s331
|
583c621de07e288cfe7689a0374081633e09a8a4
|
2022-07-09T17:20:04.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s331
| 2 | null |
transformers
| 26,791 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_vp-sv_s331
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s116
|
f3b51162eadc454c167ee9fbcb271b5dc3b0db85
|
2022-07-09T17:27:31.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_vp-sv_s116
| 2 | null |
transformers
| 26,792 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_vp-sv_s116
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s910
|
7dc449ca3f2a699c63aa7e5c3784bb93fe43be61
|
2022-07-09T17:30:44.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s910
| 2 | null |
transformers
| 26,793 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_no-pretraining_s910
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s705
|
1c5331f8041d1b170757ad4a77ea1e4401d914c9
|
2022-07-09T17:33:54.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s705
| 2 | null |
transformers
| 26,794 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_no-pretraining_s705
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s630
|
b4319b63dce12122a3a6bdce13c2f33afec6e8f4
|
2022-07-09T17:37:13.000Z
|
[
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_no-pretraining_s630
| 2 | null |
transformers
| 26,795 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_no-pretraining_s630
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s132
|
2bb4cace8906467d4d13ed1fa7dfb69ea6eddffb
|
2022-07-09T17:40:35.000Z
|
[
"pytorch",
"wavlm",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s132
| 2 | null |
transformers
| 26,796 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_wavlm_s132
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s42
|
3be6432c00778eecd9c410d3179d542df9e93e17
|
2022-07-09T17:44:00.000Z
|
[
"pytorch",
"wavlm",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s42
| 2 | null |
transformers
| 26,797 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_wavlm_s42
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s607
|
d46f6989127a8a593469ac8c987d11d3f692a68f
|
2022-07-09T17:47:17.000Z
|
[
"pytorch",
"wavlm",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_wavlm_s607
| 2 | null |
transformers
| 26,798 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_wavlm_s607
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s35
|
39886766cef5f5b9f2ccd3dbf84bfa2a0f453839
|
2022-07-09T17:50:40.000Z
|
[
"pytorch",
"unispeech",
"automatic-speech-recognition",
"sv-SE",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"license:apache-2.0"
] |
automatic-speech-recognition
| false |
jonatasgrosman
| null |
jonatasgrosman/exp_w2v2t_sv-se_unispeech-ml_s35
| 2 | null |
transformers
| 26,799 |
---
language:
- sv-SE
license: apache-2.0
tags:
- automatic-speech-recognition
- sv-SE
datasets:
- mozilla-foundation/common_voice_7_0
---
# exp_w2v2t_sv-se_unispeech-ml_s35
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (sv-SE)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
|
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