openai/whisper-base
This model is a fine-tuned version of openai/whisper-base on the pphuc25/EngMed dataset. It achieves the following results on the evaluation set:
- Loss: 1.4040
- Wer: 24.2615
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: 0.0001
- train_batch_size: 8
- 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: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7995 | 1.0 | 2268 | 0.8023 | 42.7597 |
| 0.4972 | 2.0 | 4536 | 0.8141 | 31.7847 |
| 0.3198 | 3.0 | 6804 | 0.8778 | 34.2508 |
| 0.2148 | 4.0 | 9072 | 0.9436 | 32.1119 |
| 0.1419 | 5.0 | 11340 | 1.0230 | 29.0506 |
| 0.0918 | 6.0 | 13608 | 1.0874 | 27.6792 |
| 0.0747 | 7.0 | 15876 | 1.1259 | 28.6260 |
| 0.0515 | 8.0 | 18144 | 1.1792 | 28.2198 |
| 0.0271 | 9.0 | 20412 | 1.2107 | 26.5981 |
| 0.0248 | 10.0 | 22680 | 1.2557 | 25.6329 |
| 0.0234 | 11.0 | 24948 | 1.2852 | 25.0377 |
| 0.0123 | 12.0 | 27216 | 1.2924 | 25.9923 |
| 0.0078 | 13.0 | 29484 | 1.3419 | 26.1364 |
| 0.0066 | 14.0 | 31752 | 1.3504 | 25.6874 |
| 0.003 | 15.0 | 34020 | 1.3602 | 23.9576 |
| 0.0028 | 16.0 | 36288 | 1.3710 | 24.7884 |
| 0.0045 | 17.0 | 38556 | 1.3845 | 24.4455 |
| 0.0003 | 18.0 | 40824 | 1.3914 | 25.2929 |
| 0.0002 | 19.0 | 43092 | 1.3993 | 24.3930 |
| 0.0001 | 20.0 | 45360 | 1.4040 | 24.2615 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Hanhpt23/whisper-base-engmed-v2
Base model
openai/whisper-base