whisper-base-finetuned-bmd-V1-fp16-20241111_180200-LOSO-section-out1
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: 3.6195
- Accuracy: 0.3793
- F1: 0.3333
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: 16
- eval_batch_size: 16
- seed: 1968
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 0.8571 | 3 | 1.1100 | 0.2414 | 0.1806 |
| No log | 2.0 | 7 | 1.2438 | 0.1724 | 0.1061 |
| 1.0564 | 2.8571 | 10 | 1.2948 | 0.2069 | 0.1287 |
| 1.0564 | 4.0 | 14 | 1.4553 | 0.3103 | 0.2008 |
| 1.0564 | 4.8571 | 17 | 1.6435 | 0.2759 | 0.1798 |
| 0.601 | 6.0 | 21 | 1.4658 | 0.3793 | 0.3412 |
| 0.601 | 6.8571 | 24 | 1.7203 | 0.3103 | 0.2597 |
| 0.601 | 8.0 | 28 | 1.8225 | 0.4138 | 0.4122 |
| 0.227 | 8.8571 | 31 | 1.7533 | 0.4483 | 0.4552 |
| 0.227 | 10.0 | 35 | 2.6984 | 0.3448 | 0.2730 |
| 0.227 | 10.8571 | 38 | 3.1588 | 0.2759 | 0.1850 |
| 0.0553 | 12.0 | 42 | 2.9259 | 0.4138 | 0.3870 |
| 0.0553 | 12.8571 | 45 | 2.9862 | 0.4483 | 0.4370 |
| 0.0553 | 14.0 | 49 | 3.2382 | 0.4483 | 0.4370 |
| 0.0072 | 14.8571 | 52 | 3.4094 | 0.4138 | 0.3870 |
| 0.0072 | 16.0 | 56 | 3.5602 | 0.4138 | 0.3870 |
| 0.0072 | 16.8571 | 59 | 3.6131 | 0.3793 | 0.3333 |
| 0.0034 | 17.1429 | 60 | 3.6195 | 0.3793 | 0.3333 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3