language, license, tags, datasets, model-index
| language |
license |
tags |
datasets |
model-index |
|
|
apache-2.0 |
| automatic-speech-recognition |
| mozilla-foundation/common_voice_7_0 |
| generated_from_trainer |
| robust-speech-event |
| hf-asr-leaderboard |
|
| mozilla-foundation/common_voice_7_0 |
|
| name |
results |
| XLS-R-300M - French |
| task |
dataset |
metrics |
| name |
type |
| Automatic Speech Recognition |
automatic-speech-recognition |
|
| name |
type |
args |
| Common Voice 7 |
mozilla-foundation/common_voice_7_0 |
fr |
|
| name |
type |
value |
| Test WER |
wer |
24.56 |
|
| name |
type |
value |
| Test CER |
cer |
7.3 |
|
|
|
| task |
dataset |
metrics |
| name |
type |
| Automatic Speech Recognition |
automatic-speech-recognition |
|
| name |
type |
args |
| Robust Speech Event - Dev Data |
speech-recognition-community-v2/dev_data |
fr |
|
| name |
type |
value |
| Test WER |
wer |
63.62 |
|
| name |
type |
value |
| Test CER |
cer |
17.2 |
|
|
|
| task |
dataset |
metrics |
| name |
type |
| Automatic Speech Recognition |
automatic-speech-recognition |
|
| name |
type |
args |
| Robust Speech Event - Test Data |
speech-recognition-community-v2/eval_data |
fr |
|
| name |
type |
value |
| Test WER |
wer |
66.45 |
|
|
|
|
|
|
## 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
| 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
