exp_008_base_cv24_vanilla
This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3305
- Wer: 27.1291
- Wer Ortho: 30.1229
- Cer: 8.7897
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- training_steps: 20000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho | Cer |
|---|---|---|---|---|---|---|
| 0.5773 | 0.3445 | 1000 | 0.5443 | 48.3328 | 51.3254 | 15.6376 |
| 0.4567 | 0.6889 | 2000 | 0.4493 | 39.7212 | 42.6617 | 13.2815 |
| 0.3257 | 1.0334 | 3000 | 0.3916 | 34.2850 | 37.2906 | 11.0731 |
| 0.3101 | 1.3779 | 4000 | 0.3619 | 32.8548 | 35.8135 | 11.1400 |
| 0.2987 | 1.7224 | 5000 | 0.3424 | 31.0170 | 34.0501 | 10.4724 |
| 0.2019 | 2.0668 | 6000 | 0.3367 | 29.8753 | 32.8314 | 10.0224 |
| 0.2100 | 2.4113 | 7000 | 0.3303 | 28.9296 | 32.0212 | 9.7600 |
| 0.2068 | 2.7558 | 8000 | 0.3193 | 27.9595 | 31.0167 | 9.0057 |
| 0.1307 | 3.1002 | 9000 | 0.3343 | 27.9822 | 31.0302 | 9.1302 |
| 0.1381 | 3.4447 | 10000 | 0.3335 | 27.8125 | 30.8133 | 8.9957 |
| 0.1353 | 3.7892 | 11000 | 0.3305 | 27.1291 | 30.1229 | 8.7897 |
| 0.0784 | 4.1337 | 12000 | 0.3474 | 27.5965 | 30.7395 | 9.0974 |
| 0.0785 | 4.4781 | 13000 | 0.3553 | 27.3914 | 30.3821 | 8.9799 |
| 0.0761 | 4.8226 | 14000 | 0.3551 | 27.4994 | 30.4820 | 8.9953 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2