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# wav2vec2-large-xls-r-300m-finnish

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - FI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2307
- Wer: 0.2984

## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 70.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9032        | 4.39  | 500  | 2.8768          | 1.0    |
| 1.5724        | 8.77  | 1000 | 0.5638          | 0.6438 |
| 1.1818        | 13.16 | 1500 | 0.3338          | 0.4759 |
| 1.0798        | 17.54 | 2000 | 0.2876          | 0.4086 |
| 1.0296        | 21.93 | 2500 | 0.2694          | 0.4248 |
| 1.0014        | 26.32 | 3000 | 0.2626          | 0.3733 |
| 0.9616        | 30.7  | 3500 | 0.2391          | 0.3294 |
| 0.9303        | 35.09 | 4000 | 0.2352          | 0.3218 |
| 0.9248        | 39.47 | 4500 | 0.2351          | 0.3207 |
| 0.8837        | 43.86 | 5000 | 0.2341          | 0.3103 |
| 0.8887        | 48.25 | 5500 | 0.2311          | 0.3115 |
| 0.8529        | 52.63 | 6000 | 0.2230          | 0.3001 |
| 0.8404        | 57.02 | 6500 | 0.2279          | 0.3054 |
| 0.8242        | 61.4  | 7000 | 0.2298          | 0.3006 |
| 0.8288        | 65.79 | 7500 | 0.2333          | 0.2997 |


### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0

{"language": ["fi"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fi", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Finnish", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 7", "type": "mozilla-foundation/common_voice_7_0", "args": "fi"}, "metrics": [{"type": "wer", "value": 29.97, "name": "Test WER"}, {"type": "cer", "value": "NA", "name": "Test CER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition fi generated_from_trainer hf-asr-leaderboard model_for_talk mozilla-foundation/common_voice_7_0 robust-speech-event dataset:mozilla-foundation/common_voice_7_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fi #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

wav2vec2-large-xls-r-300m-finnish
=================================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - FI dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2307
* Wer: 0.2984


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: 7e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 70.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 70.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fi #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 70.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fi #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 70.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0