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wav2vec2-base-2
This model is a fine-tuned version of jiobiala24/wav2vec2-base-1 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.9415
- Wer: 0.3076
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: 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
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4206 | 1.96 | 1000 | 0.6022 | 0.3435 |
| 0.3278 | 3.93 | 2000 | 0.6191 | 0.3344 |
| 0.2604 | 5.89 | 3000 | 0.6170 | 0.3288 |
| 0.2135 | 7.86 | 4000 | 0.6590 | 0.3239 |
| 0.1805 | 9.82 | 5000 | 0.7359 | 0.3289 |
| 0.1582 | 11.79 | 6000 | 0.7450 | 0.3276 |
| 0.1399 | 13.75 | 7000 | 0.7914 | 0.3218 |
| 0.1252 | 15.72 | 8000 | 0.8254 | 0.3185 |
| 0.1095 | 17.68 | 9000 | 0.8524 | 0.3184 |
| 0.1 | 19.65 | 10000 | 0.8340 | 0.3165 |
| 0.0905 | 21.61 | 11000 | 0.8846 | 0.3161 |
| 0.0819 | 23.58 | 12000 | 0.8994 | 0.3142 |
| 0.0763 | 25.54 | 13000 | 0.9018 | 0.3134 |
| 0.0726 | 27.5 | 14000 | 0.9552 | 0.3081 |
| 0.0668 | 29.47 | 15000 | 0.9415 | 0.3076 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3
