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dat259-cv_en-wav2vec2
This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_1_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.4286
- Wer: 0.5339
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.383 | 1.32 | 200 | 3.0312 | 1.0 |
| 2.7346 | 2.63 | 400 | 2.0207 | 0.9413 |
| 0.8772 | 3.95 | 600 | 1.3528 | 0.6911 |
| 0.4718 | 5.26 | 800 | 1.1830 | 0.6135 |
| 0.3209 | 6.58 | 1000 | 1.2242 | 0.5856 |
| 0.2556 | 7.89 | 1200 | 1.3165 | 0.5894 |
| 0.2055 | 9.21 | 1400 | 1.3716 | 0.5708 |
| 0.18 | 10.53 | 1600 | 1.2709 | 0.5702 |
| 0.1497 | 11.84 | 1800 | 1.4300 | 0.5526 |
| 0.126 | 13.16 | 2000 | 1.3852 | 0.5507 |
| 0.1145 | 14.47 | 2200 | 1.3893 | 0.5489 |
| 0.101 | 15.79 | 2400 | 1.4051 | 0.5431 |
| 0.091 | 17.11 | 2600 | 1.4103 | 0.5399 |
| 0.0793 | 18.42 | 2800 | 1.3968 | 0.5324 |
| 0.0746 | 19.74 | 3000 | 1.4286 | 0.5339 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1
