whisper-a-nomi-ls
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0301
- Wer: 97.3190
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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 11
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 1.0 | 88 | 0.2173 | 32.7078 |
| 0.9256 | 2.0 | 176 | 0.0358 | 13.6729 |
| 0.1103 | 3.0 | 264 | 0.1075 | 45.6658 |
| 0.0399 | 4.0 | 352 | 0.0939 | 68.9008 |
| 0.0319 | 5.0 | 440 | 0.0241 | 19.1242 |
| 0.0144 | 6.0 | 528 | 0.0252 | 18.2306 |
| 0.01 | 7.0 | 616 | 0.0300 | 99.3744 |
| 0.0023 | 8.0 | 704 | 0.0268 | 97.9446 |
| 0.0023 | 9.0 | 792 | 0.0301 | 97.3190 |
| 0.0003 | 10.0 | 880 | 0.0301 | 97.3190 |
| 0.0 | 11.0 | 968 | 0.0301 | 97.3190 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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Base model
openai/whisper-small