Whisper Small Ro - VM6
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: 0.9801
- Wer: 44.7801
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
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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: 150
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.05 | 3.69 | 1000 | 0.8344 | 50.6543 |
| 0.0077 | 7.38 | 2000 | 0.9303 | 44.9572 |
| 0.0043 | 11.07 | 3000 | 0.9479 | 48.7848 |
| 0.0008 | 14.76 | 4000 | 0.9801 | 44.7801 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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Model tree for VMadalina/whisper-small-music2text2-protv-music-finetuned
Base model
openai/whisper-small