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wav2vec2-large-xls-r-300m-french-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.4075
- Wer: 0.2074
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.4642 | 1.07 | 400 | 1.4491 | 0.8681 |
| 0.9543 | 2.14 | 800 | 0.5998 | 0.4982 |
| 0.5364 | 3.21 | 1200 | 0.4400 | 0.3549 |
| 0.4236 | 4.28 | 1600 | 0.4348 | 0.3476 |
| 0.3345 | 5.35 | 2000 | 0.3897 | 0.3000 |
| 0.2938 | 6.42 | 2400 | 0.3893 | 0.3176 |
| 0.2502 | 7.49 | 2800 | 0.4306 | 0.3000 |
| 0.2376 | 8.56 | 3200 | 0.4023 | 0.2939 |
| 0.1999 | 9.63 | 3600 | 0.3973 | 0.2652 |
| 0.1859 | 10.7 | 4000 | 0.3701 | 0.2773 |
| 0.1673 | 11.76 | 4400 | 0.4047 | 0.2661 |
| 0.1555 | 12.83 | 4800 | 0.4207 | 0.2670 |
| 0.1385 | 13.9 | 5200 | 0.4110 | 0.2700 |
| 0.13 | 14.97 | 5600 | 0.4209 | 0.2575 |
| 0.1185 | 16.04 | 6000 | 0.4385 | 0.2582 |
| 0.11 | 17.11 | 6400 | 0.4334 | 0.2461 |
| 0.1016 | 18.18 | 6800 | 0.4058 | 0.2450 |
| 0.0913 | 19.25 | 7200 | 0.3923 | 0.2439 |
| 0.0843 | 20.32 | 7600 | 0.4139 | 0.2434 |
| 0.0782 | 21.39 | 8000 | 0.4111 | 0.2397 |
| 0.0732 | 22.46 | 8400 | 0.4116 | 0.2327 |
| 0.0644 | 23.53 | 8800 | 0.4041 | 0.2327 |
| 0.0603 | 24.6 | 9200 | 0.4065 | 0.2232 |
| 0.0553 | 25.67 | 9600 | 0.4198 | 0.2198 |
| 0.0502 | 26.74 | 10000 | 0.4137 | 0.2172 |
| 0.0472 | 27.81 | 10400 | 0.4084 | 0.2148 |
| 0.0455 | 28.88 | 10800 | 0.4116 | 0.2109 |
| 0.0417 | 29.95 | 11200 | 0.4075 | 0.2074 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
