whisper-swi-asr_new2
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1832
- Wer: 0.0890
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: 2e-05
- 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: 50
- training_steps: 16000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3675 | 0.2219 | 1000 | 0.3479 | 0.2085 |
| 0.2826 | 0.4439 | 2000 | 0.2770 | 0.1661 |
| 0.2485 | 0.6658 | 3000 | 0.2378 | 0.1863 |
| 0.2316 | 0.8877 | 4000 | 0.2140 | 0.1715 |
| 0.1103 | 1.1096 | 5000 | 0.2161 | 0.1470 |
| 0.1064 | 1.3316 | 6000 | 0.2054 | 0.1268 |
| 0.1011 | 1.5535 | 7000 | 0.2017 | 0.1141 |
| 0.0934 | 1.7754 | 8000 | 0.1868 | 0.1268 |
| 0.0968 | 1.9973 | 9000 | 0.1811 | 0.1054 |
| 0.0389 | 2.2193 | 10000 | 0.1925 | 0.1208 |
| 0.0384 | 2.4412 | 11000 | 0.1878 | 0.1029 |
| 0.0346 | 2.6631 | 12000 | 0.1789 | 0.1081 |
| 0.0304 | 2.8850 | 13000 | 0.1755 | 0.1078 |
| 0.0131 | 3.1070 | 14000 | 0.1814 | 0.0890 |
| 0.0098 | 3.3289 | 15000 | 0.1837 | 0.1062 |
| 0.0079 | 3.5508 | 16000 | 0.1832 | 0.0890 |
Framework versions
- Transformers 4.43.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1