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# wav2vec2-base-gn-demo

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7426
- Wer: 0.7256

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 50
- num_epochs: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 4.0   | 100  | 0.7045          | 0.7409 |
| No log        | 8.0   | 200  | 0.7200          | 0.75   |
| No log        | 12.0  | 300  | 0.7400          | 0.7439 |
| No log        | 16.0  | 400  | 0.7677          | 0.7515 |
| 0.0846        | 20.0  | 500  | 0.7765          | 0.7271 |
| 0.0846        | 24.0  | 600  | 0.7821          | 0.7287 |
| 0.0846        | 28.0  | 700  | 0.7671          | 0.7180 |
| 0.0846        | 32.0  | 800  | 0.7594          | 0.7180 |
| 0.0846        | 36.0  | 900  | 0.7500          | 0.7165 |
| 0.0713        | 40.0  | 1000 | 0.7351          | 0.7287 |
| 0.0713        | 44.0  | 1100 | 0.7361          | 0.7241 |
| 0.0713        | 48.0  | 1200 | 0.7389          | 0.7378 |
| 0.0713        | 52.0  | 1300 | 0.7424          | 0.7210 |
| 0.0713        | 56.0  | 1400 | 0.7425          | 0.7256 |
| 0.0669        | 60.0  | 1500 | 0.7426          | 0.7256 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.10.3

{"language": ["gn"], "license": "apache-2.0", "tags": ["generated_from_trainer", "mozilla-foundation/common_voice_8_0", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["common_voice", "mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-base-gn-demo", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer mozilla-foundation/common_voice_8_0 robust-speech-event hf-asr-leaderboard gn dataset:common_voice dataset:mozilla-foundation/common_voice_8_0 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #mozilla-foundation/common_voice_8_0 #robust-speech-event #hf-asr-leaderboard #gn #dataset-common_voice #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-base-gn-demo
=====================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice dataset.
It achieves the following results on the evaluation set:


* Loss: 0.7426
* Wer: 0.7256


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: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 50
* num\_epochs: 60
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 50
* num\_epochs: 60
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #mozilla-foundation/common_voice_8_0 #robust-speech-event #hf-asr-leaderboard #gn #dataset-common_voice #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 50
* num\_epochs: 60
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #mozilla-foundation/common_voice_8_0 #robust-speech-event #hf-asr-leaderboard #gn #dataset-common_voice #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine\_with\_restarts
* lr\_scheduler\_warmup\_steps: 50
* num\_epochs: 60
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3