whisper-small-atco2-asr
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8297
- Wer: 33.4520
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6955 | 12.5 | 50 | 0.8441 | 57.4288 |
| 0.0631 | 25.0 | 100 | 0.7271 | 27.8470 |
| 0.0034 | 37.5 | 150 | 0.7708 | 36.8772 |
| 0.0008 | 50.0 | 200 | 0.7991 | 31.8060 |
| 0.0006 | 62.5 | 250 | 0.8141 | 32.2509 |
| 0.0004 | 75.0 | 300 | 0.8228 | 32.8292 |
| 0.0004 | 87.5 | 350 | 0.8281 | 33.2295 |
| 0.0004 | 100.0 | 400 | 0.8297 | 33.4520 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0