metadata
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- robust-speech-event
model-index:
- name: XLS-R-1B - French
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: fr
metrics:
- name: Test WER
type: wer
value: 21.65
- name: Test CER
type: cer
value: 6.52
- 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: 61.72
- name: Test CER
type: cer
value: 16.43
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 and evaluation data
It achieves the following results on the evaluation set (Step 17000):
- Wer: 0.2172
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
- 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 |
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