whisper-small-reverse-ml-mft-1-single-gpu
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0807
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: 0.0002
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 593
- training_steps: 5928
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0 | 0 | 1.9155 |
| 0.0967 | 1.0 | 1482 | 0.0975 |
| 0.0525 | 2.0 | 2964 | 0.0825 |
| 0.0294 | 3.0 | 4446 | 0.0806 |
| 0.0254 | 4.0 | 5928 | 0.0807 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.8.0+cu128
- Datasets 4.4.1
- Tokenizers 0.21.4
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Model tree for kavyamanohar/whisper-small-reverse-ml-mft-1-single-gpu
Base model
openai/whisper-small