whisper-large-v2-atcosim
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0552
- Wer: 9.9694
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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 12500
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0038 | 8.33 | 1000 | 0.0357 | 2.7829 |
| 0.001 | 16.67 | 2000 | 0.0384 | 2.0004 |
| 0.0015 | 25.0 | 3000 | 0.0373 | 31.7142 |
| 0.0001 | 33.33 | 4000 | 0.0437 | 2.3152 |
| 0.0019 | 41.67 | 5000 | 0.0446 | 7.2375 |
| 0.0 | 50.0 | 6000 | 0.0462 | 2.9033 |
| 0.0 | 58.33 | 7000 | 0.0490 | 4.3295 |
| 0.0 | 66.67 | 8000 | 0.0509 | 5.8668 |
| 0.0 | 75.0 | 9000 | 0.0524 | 7.5014 |
| 0.0 | 83.33 | 10000 | 0.0536 | 8.6405 |
| 0.0 | 91.67 | 11000 | 0.0546 | 9.5018 |
| 0.0 | 100.0 | 12000 | 0.0552 | 9.9694 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3