open-ai-small-4
This model is a fine-tuned version of jadasdn/open-ai-small-3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4644
- Wer: 26.0796
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: 1e-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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1913 | 2.0 | 1000 | 0.3365 | 17.8086 |
0.0189 | 4.0 | 2000 | 0.4064 | 17.3732 |
0.003 | 6.0 | 3000 | 0.4513 | 23.2204 |
0.0016 | 8.0 | 4000 | 0.4644 | 26.0796 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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