./200
This model is a fine-tuned version of openai/whisper-medium.en on the 200 SF 200 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8389
- Wer Ortho: 35.1676
- Wer: 23.8967
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: 800
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
1.5629 | 8.0 | 100 | 1.1016 | 41.3994 | 29.9964 |
0.7012 | 16.0 | 200 | 0.8286 | 36.0787 | 25.1525 |
0.4369 | 24.0 | 300 | 0.8091 | 36.1152 | 25.3678 |
0.3073 | 32.0 | 400 | 0.8257 | 34.7303 | 23.7890 |
0.2298 | 40.0 | 500 | 0.8354 | 34.8397 | 22.8920 |
0.1938 | 48.0 | 600 | 0.8306 | 35.4592 | 23.4661 |
0.1658 | 56.0 | 700 | 0.8359 | 35.5321 | 23.8967 |
0.1534 | 64.0 | 800 | 0.8389 | 35.1676 | 23.8967 |
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-200
Base model
openai/whisper-medium.en