w2v-fine-tune-test-no-punct4
This model is a fine-tuned version of ylacombe/w2v-bert-2.0 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0213
- Wer: 0.888
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: 16
- 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: 20
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.5721 | 1.54 | 20 | 3.5316 | 1.0 |
| 3.3513 | 3.08 | 40 | 3.3113 | 1.0 |
| 2.9765 | 4.62 | 60 | 3.1604 | 1.016 |
| 2.0468 | 6.15 | 80 | 2.5162 | 1.02 |
| 0.8977 | 7.69 | 100 | 1.4944 | 1.008 |
| 0.3831 | 9.23 | 120 | 1.0213 | 0.888 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Base model
ylacombe/w2v-bert-2.0