
## Model description

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_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: 5.0 (extended to 7.0 with training with checkpoint)
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 2.9114        | 0.29  | 1000  | inf             | 0.9997 |
| 1.2436        | 0.57  | 2000  | inf             | 0.4310 |
| 1.0552        | 0.86  | 3000  | inf             | 0.3144 |
| 1.0044        | 1.15  | 4000  | inf             | 0.2814 |
| 0.9718        | 1.43  | 5000  | inf             | 0.2658 |
| 0.9502        | 1.72  | 6000  | inf             | 0.2566 |
| 0.9418        | 2.01  | 7000  | inf             | 0.2476 |
| 0.9215        | 2.29  | 8000  | inf             | 0.2420 |
| 0.9236        | 2.58  | 9000  | inf             | 0.2388 |
| 0.9014        | 2.87  | 10000 | inf             | 0.2354 |
| 0.8814        | 3.15  | 11000 | inf             | 0.2312 |
| 0.8809        | 3.44  | 12000 | inf             | 0.2285 |
| 0.8717        | 3.73  | 13000 | inf             | 0.2263 |
| 0.8787        | 4.01  | 14000 | inf             | 0.2218 |
| 0.8567        | 4.3   | 15000 | inf             | 0.2193 |
| 0.8488        | 4.59  | 16000 | inf             | 0.2187 |
| 0.8359        | 4.87  | 17000 | inf             | 0.2172 |

Training continued with checkpoint from STEP 17000:

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| /             | 5.16  | 18000 | inf             | 0.2176 |
| /             | 5.45  | 19000 | inf             | 0.2181 |
| /             | 5.73  | 20000 | inf             | 0.2155 |
| /             | 6.02  | 21000 | inf             | 0.2140 |
| /             | 6.31  | 22000 | inf             | 0.2124 |
| /             | 6.59  | 23000 | inf             | 0.2117 |
| /             | 6.88  | 24000 | inf             | 0.2116 |


It achieves the best result on the validation set on Step 24000:
- Wer: 0.2116

Got some issue with validation loss calculation.

### 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-300m-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-300m-cv_8-fr --dataset speech-recognition-community-v2/dev_data --config fr --split validation --chunk_length_s 5.0 --stride_length_s 1.0
```

{"language": ["fr"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer"], "model-index": [{"name": "XLS-R-300m - 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": "to recompute with STEP 24000", "name": "Test WER"}, {"type": "cer", "value": "to recompute with STEP 24000", "name": "Test CER"}]}, {"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": 35.29, "name": "Test WER"}, {"type": "cer", "value": 13.94, "name": "Test CER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_8_0 generated_from_trainer fr 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 #fr #license-apache-2.0 #model-index #endpoints_compatible #region-us 

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


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m 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: 5.0 (extended to 7.0 with training with checkpoint)
* mixed\_precision\_training: Native AMP


### Training results



Training continued with checkpoint from STEP 17000:



It achieves the best result on the validation set on Step 24000:


* Wer: 0.2116


Got some issue with validation loss calculation.


### 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'



### 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: 5.0 (extended to 7.0 with training with checkpoint)
* mixed\_precision\_training: Native AMP ### Training results



Training continued with checkpoint from STEP 17000:



It achieves the best result on the validation set on Step 24000:


* Wer: 0.2116


Got some issue with validation loss calculation. ### 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'
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #fr #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: 5.0 (extended to 7.0 with training with checkpoint)
* mixed\_precision\_training: Native AMP ### Training results



Training continued with checkpoint from STEP 17000:



It achieves the best result on the validation set on Step 24000:


* Wer: 0.2116


Got some issue with validation loss calculation. ### 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'
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #fr #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: 5.0 (extended to 7.0 with training with checkpoint)
* mixed\_precision\_training: Native AMP### Training results



Training continued with checkpoint from STEP 17000:



It achieves the best result on the validation set on Step 24000:


* Wer: 0.2116


Got some issue with validation loss calculation.### 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'