xls-r-300m-fr / README.md
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---
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:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: fr
metrics:
- name: Test WER
type: wer
value: 24.56
- name: Test CER
type: cer
value: 7.3
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: fr
metrics:
- name: Test WER
type: wer
value: 63.62
- name: Test CER
type: cer
value: 17.2
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: fr
metrics:
- name: Test WER
type: wer
value: 66.45
---
---
<!-- 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
```