---

<!-- 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. -->

## 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_7_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: 2.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.495         | 0.16  | 500  | 3.3883          | 1.0    |
| 2.9095        | 0.32  | 1000 | 2.9152          | 1.0000 |
| 1.8434        | 0.49  | 1500 | 1.0473          | 0.7446 |
| 1.4298        | 0.65  | 2000 | 0.5729          | 0.5130 |
| 1.1937        | 0.81  | 2500 | 0.3795          | 0.3450 |
| 1.1248        | 0.97  | 3000 | 0.3321          | 0.3052 |
| 1.0835        | 1.13  | 3500 | 0.3038          | 0.2805 |
| 1.0479        | 1.3   | 4000 | 0.2910          | 0.2689 |
| 1.0413        | 1.46  | 4500 | 0.2798          | 0.2593 |
| 1.014         | 1.62  | 5000 | 0.2727          | 0.2512 |
| 1.004         | 1.78  | 5500 | 0.2646          | 0.2471 |
| 0.9949        | 1.94  | 6000 | 0.2619          | 0.2457 |

It achieves the best result on STEP 6000 on the validation set:
- Loss: 0.2619
- Wer: 0.2457

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0

### Evaluation Commands
1. To evaluate on `mozilla-foundation/common_voice_7` with split `test`

```bash
python eval.py --model_id Plim/xls-r-300m-fr --dataset mozilla-foundation/common_voice_7_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-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_7_0", "generated_from_trainer", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - French", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 7", "type": "mozilla-foundation/common_voice_7_0", "args": "fr"}, "metrics": [{"type": "wer", "value": 24.56, "name": "Test WER"}, {"type": "cer", "value": 7.3, "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": 63.62, "name": "Test WER"}, {"type": "cer", "value": 17.2, "name": "Test CER"}]}, {"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": 66.45, "name": "Test WER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_7_0 generated_from_trainer robust-speech-event hf-asr-leaderboard fr dataset:mozilla-foundation/common_voice_7_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #fr #dataset-mozilla-foundation/common_voice_7_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-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_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: 2.0
* mixed\_precision\_training: Native AMP


### Training results



It achieves the best result on STEP 6000 on the validation set:


* Loss: 0.2619
* Wer: 0.2457


### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0


### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_7' 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: 2.0
* mixed\_precision\_training: Native AMP ### Training results



It achieves the best result on STEP 6000 on the validation set:


* Loss: 0.2619
* Wer: 0.2457 ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0 ### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_7' with split 'test'
2. To evaluate on 'speech-recognition-community-v2/dev\_data'
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #fr #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: 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: 2.0
* mixed\_precision\_training: Native AMP ### Training results



It achieves the best result on STEP 6000 on the validation set:


* Loss: 0.2619
* Wer: 0.2457 ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0 ### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_7' 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_7_0 #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #fr #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: 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: 2.0
* mixed\_precision\_training: Native AMP### Training results



It achieves the best result on STEP 6000 on the validation set:


* Loss: 0.2619
* Wer: 0.2457### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_7' with split 'test'
2. To evaluate on 'speech-recognition-community-v2/dev\_data'