
## Model description

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 6.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.9827        | 0.29  | 1000  | inf             | 0.2937 |
| 1.0203        | 0.57  | 2000  | inf             | 0.2711 |
| 1.0048        | 0.86  | 3000  | inf             | 0.2620 |
| 0.9858        | 1.15  | 4000  | inf             | 0.2522 |
| 0.9709        | 1.43  | 5000  | inf             | 0.2365 |
| 0.9347        | 1.72  | 6000  | inf             | 0.2332 |
| 0.9256        | 2.01  | 7000  | inf             | 0.2261 |
| 0.8936        | 2.29  | 8000  | inf             | 0.2203 |
| 0.877         | 2.58  | 9000  | inf             | 0.2096 |
| 0.8393        | 2.87  | 10000 | inf             | 0.2017 |
| 0.8156        | 3.15  | 11000 | inf             | 0.1936 |
| 0.8015        | 3.44  | 12000 | inf             | 0.1880 |
| 0.774         | 3.73  | 13000 | inf             | 0.1834 |
| 0.8372        | 4.01  | 14000 | inf             | 0.1934 |
| 0.8075        | 4.3   | 15000 | inf             | 0.1923 |
| 0.8069        | 4.59  | 16000 | inf             | 0.1877 |
| 0.8064        | 4.87  | 17000 | inf             | 0.1955 |
| 0.801         | 5.16  | 18000 | inf             | 0.1891 |
| 0.8022        | 5.45  | 19000 | inf             | 0.1895 |
| 0.792         | 5.73  | 20000 | inf             | 0.1854 |

It achieves the best result on the validation set on STEP 13000:
- Wer: 0.1834

Some problem occurs when calculating the validation loss.

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3.dev0
- Tokenizers 0.11.0

### Evaluation Commands
1. To evaluate on `mozilla-foundation/common_voice_8` with split `test`
```bash
python eval.py --model_id Plim/xls-r-1b-cv_8-fr --dataset mozilla-foundation/common_voice_8_0 --config fr --split test
```
2. To evaluate on `speech-recognition-community-v2/dev_data`
```bash
python eval.py --model_id Plim/xls-r-1b-cv_8-fr --dataset speech-recognition-community-v2/dev_data --config fr --split validation --chunk_length_s 5.0 --stride_length_s 1.0
```

### Evaluation Results

Without LM:

| Dataset    | WER   | CER   |
|:----------:|:-----:|:-----:|
| TEST CV    | 18.33 | 5.60  |
| DEV audio  | 31.33 | 13.20 |
| TEST audio | /     | /     |

With LM:

| Dataset    | WER   | CER   |
|:----------:|:-----:|:-----:|
| TEST CV    | 15.40 | 5.36  |
| DEV audio  | 25.05 | 12.45 |
| TEST audio | /     | /     |

{"language": ["fr"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R-1B - French", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "fr"}, "metrics": [{"type": "wer", "value": 15.4, "name": "Test WER (with LM)"}, {"type": "cer", "value": 5.36, "name": "Test CER (with LM)"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Dev Data", "type": "speech-recognition-community-v2/dev_data", "args": "fr"}, "metrics": [{"type": "wer", "value": 25.05, "name": "Test WER (with LM)"}, {"type": "cer", "value": 12.45, "name": "Test CER (with LM)"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Test Data", "type": "speech-recognition-community-v2/eval_data", "args": "fr"}, "metrics": [{"type": "wer", "value": 27.1, "name": "Test WER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_8_0 generated_from_trainer robust-speech-event hf-asr-leaderboard fr dataset:mozilla-foundation/common_voice_8_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #fr #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

Model description
-----------------


This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - FR dataset.


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 6.0
* mixed\_precision\_training: Native AMP


### Training results



It achieves the best result on the validation set on STEP 13000:


* Wer: 0.1834


Some problem occurs when calculating the validation loss.


### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3.dev0
* Tokenizers 0.11.0


### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_8' with split 'test'
2. To evaluate on 'speech-recognition-community-v2/dev\_data'


### Evaluation Results


Without LM:



With LM:




### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 6.0
* mixed\_precision\_training: Native AMP ### Training results



It achieves the best result on the validation set on STEP 13000:


* Wer: 0.1834


Some problem occurs when calculating the validation loss. ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3.dev0
* Tokenizers 0.11.0 ### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_8' with split 'test'
2. To evaluate on 'speech-recognition-community-v2/dev\_data' ### Evaluation Results


Without LM:



With LM:
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #fr #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 6.0
* mixed\_precision\_training: Native AMP ### Training results



It achieves the best result on the validation set on STEP 13000:


* Wer: 0.1834


Some problem occurs when calculating the validation loss. ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3.dev0
* Tokenizers 0.11.0 ### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_8' with split 'test'
2. To evaluate on 'speech-recognition-community-v2/dev\_data' ### Evaluation Results


Without LM:



With LM:
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #fr #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 6.0
* mixed\_precision\_training: Native AMP### Training results



It achieves the best result on the validation set on STEP 13000:


* Wer: 0.1834


Some problem occurs when calculating the validation loss.### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.3.dev0
* Tokenizers 0.11.0### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_8' with split 'test'
2. To evaluate on 'speech-recognition-community-v2/dev\_data'### Evaluation Results


Without LM:



With LM: