w2v2-base-pretrained_lr5e-5_at0.1_da1
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1584
- Wer: 0.1683
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
19.3795 | 3.91 | 250 | 4.4039 | 1.0 |
3.4426 | 7.81 | 500 | 3.2239 | 1.0 |
3.1246 | 11.72 | 750 | 3.1005 | 1.0 |
2.3409 | 15.62 | 1000 | 1.0214 | 0.8765 |
0.6128 | 19.53 | 1250 | 0.6213 | 0.4643 |
0.3506 | 23.44 | 1500 | 0.6847 | 0.2409 |
0.2498 | 27.34 | 1750 | 0.7219 | 0.2055 |
0.1928 | 31.25 | 2000 | 0.9377 | 0.1730 |
0.1689 | 35.16 | 2250 | 1.0552 | 0.1794 |
0.1437 | 39.06 | 2500 | 0.9440 | 0.1756 |
0.1256 | 42.97 | 2750 | 1.1132 | 0.1721 |
0.1199 | 46.88 | 3000 | 1.1349 | 0.1777 |
0.1087 | 50.78 | 3250 | 1.0542 | 0.1781 |
0.1056 | 54.69 | 3500 | 1.1394 | 0.1696 |
0.1006 | 58.59 | 3750 | 1.1261 | 0.1696 |
0.0933 | 62.5 | 4000 | 1.1584 | 0.1683 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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