w2v2-base-pretrained_lr5e-5_at0.8_da0.8
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: 2.2369
- Wer: 0.1717
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 |
---|---|---|---|---|
18.8283 | 6.76 | 250 | 4.1824 | 1.0 |
3.3429 | 13.51 | 500 | 3.2478 | 1.0 |
3.1004 | 20.27 | 750 | 3.1282 | 1.0 |
1.8593 | 27.03 | 1000 | 1.1074 | 0.4259 |
0.2428 | 33.78 | 1250 | 1.2176 | 0.2166 |
0.1279 | 40.54 | 1500 | 1.6077 | 0.1931 |
0.0893 | 47.3 | 1750 | 1.7647 | 0.1867 |
0.0669 | 54.05 | 2000 | 1.9817 | 0.1815 |
0.0527 | 60.81 | 2250 | 2.0652 | 0.1803 |
0.0458 | 67.57 | 2500 | 2.1288 | 0.1850 |
0.0408 | 74.32 | 2750 | 1.9809 | 0.1786 |
0.0345 | 81.08 | 3000 | 2.0693 | 0.1833 |
0.031 | 87.84 | 3250 | 2.3649 | 0.1798 |
0.0277 | 94.59 | 3500 | 2.3239 | 0.1721 |
0.0279 | 101.35 | 3750 | 2.1769 | 0.1730 |
0.0263 | 108.11 | 4000 | 2.2369 | 0.1717 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
- Downloads last month
- 1