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Whisper Base Ta - Bharat Ramanathan
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2269
- Wer: 21.7243
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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5559 | 0.1 | 1000 | 0.3963 | 35.3308 |
| 0.3891 | 0.2 | 2000 | 0.3146 | 29.1511 |
| 0.3425 | 0.3 | 3000 | 0.2834 | 25.5930 |
| 0.3108 | 0.1 | 4000 | 0.2669 | 24.7191 |
| 0.2866 | 0.1 | 5000 | 0.2596 | 25.0936 |
| 0.2697 | 0.2 | 6000 | 0.2507 | 24.5943 |
| 0.2421 | 0.05 | 6500 | 0.2411 | 23.0395 |
| 0.2425 | 0.1 | 7000 | 0.2370 | 23.3804 |
| 0.2404 | 0.15 | 7500 | 0.2333 | 22.7959 |
| 0.2381 | 0.2 | 8000 | 0.2311 | 22.9420 |
| 0.2429 | 0.25 | 8500 | 0.2305 | 22.0166 |
| 0.2402 | 0.3 | 9000 | 0.2284 | 22.1140 |
| 0.2377 | 0.35 | 9500 | 0.2271 | 22.0653 |
| 0.2389 | 0.4 | 10000 | 0.2269 | 21.7243 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
