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whisper-medium-amksim
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9089
- Wer: 40.3433
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.6349 | 0.83 | 5 | 3.7729 | 73.3906 |
| 3.2338 | 1.67 | 10 | 1.4978 | 69.0987 |
| 1.1335 | 2.5 | 15 | 1.1606 | 97.4249 |
| 0.6838 | 3.33 | 20 | 1.0211 | 66.0944 |
| 0.4383 | 4.17 | 25 | 0.9845 | 65.2361 |
| 0.2514 | 5.0 | 30 | 0.9885 | 61.3734 |
| 0.2053 | 5.83 | 35 | 0.9796 | 76.3948 |
| 0.1353 | 6.67 | 40 | 0.9758 | 49.3562 |
| 0.1142 | 7.5 | 45 | 0.9109 | 60.9442 |
| 0.0889 | 8.33 | 50 | 0.9045 | 41.2017 |
| 0.0854 | 9.17 | 55 | 0.9085 | 42.4893 |
| 0.069 | 10.0 | 60 | 0.9089 | 40.3433 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.12.1
