./400
This model is a fine-tuned version of openai/whisper-medium.en on the 400 SF 1000 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7217
- Wer Ortho: 29.6283
- Wer: 19.5551
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.6015 | 4.0 | 100 | 1.1045 | 41.2901 | 30.3911 |
| 0.8237 | 8.0 | 200 | 0.7959 | 31.3776 | 20.4880 |
| 0.5824 | 12.0 | 300 | 0.7417 | 29.7741 | 19.3757 |
| 0.4724 | 16.0 | 400 | 0.7256 | 29.5554 | 19.4474 |
| 0.4232 | 20.0 | 500 | 0.7217 | 29.6283 | 19.5551 |
Framework versions
- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Makkoen/whisper-medium.en-cit-do015-wd0-lr1e-06-SF-400
Base model
openai/whisper-medium.en