w2v2-base-pretrained_lr5e-5_at1_da1-p4
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: 0.6341
- Wer: 0.1039
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 |
---|---|---|---|---|
18.6256 | 5.21 | 250 | 4.2622 | 1.0 |
3.3901 | 10.42 | 500 | 3.2209 | 1.0 |
3.0963 | 15.62 | 750 | 3.1175 | 1.0 |
2.0992 | 20.83 | 1000 | 0.5962 | 0.4402 |
0.2069 | 26.04 | 1250 | 0.4456 | 0.1310 |
0.0849 | 31.25 | 1500 | 0.4902 | 0.1200 |
0.0596 | 36.46 | 1750 | 0.5079 | 0.1176 |
0.0437 | 41.67 | 2000 | 0.5362 | 0.1136 |
0.0355 | 46.88 | 2250 | 0.5433 | 0.1156 |
0.0281 | 52.08 | 2500 | 0.5994 | 0.1136 |
0.0238 | 57.29 | 2750 | 0.6018 | 0.1112 |
0.02 | 62.5 | 3000 | 0.5970 | 0.1120 |
0.0181 | 67.71 | 3250 | 0.6282 | 0.1083 |
0.0167 | 72.92 | 3500 | 0.6120 | 0.1075 |
0.0145 | 78.12 | 3750 | 0.6404 | 0.1047 |
0.014 | 83.33 | 4000 | 0.6341 | 0.1039 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for MelanieKoe/w2v2-base-pretrained_lr5e-5_at1_da1-p4
Base model
facebook/wav2vec2-base