whisper-medium-bigcgen-combined-5hrs-62
This model is a fine-tuned version of openai/whisper-medium on the bigcgen dataset. It achieves the following results on the evaluation set:
- Loss: 0.7209
- Wer: 0.5565
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: 2
- eval_batch_size: 2
- seed: 62
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.0959 | 0.6079 | 200 | 0.9655 | 0.6610 |
0.6562 | 1.2158 | 400 | 0.8052 | 0.5699 |
0.6063 | 1.8237 | 600 | 0.7209 | 0.5565 |
0.402 | 2.4316 | 800 | 0.7347 | 0.5566 |
0.3066 | 3.0395 | 1000 | 0.7320 | 0.5467 |
0.2262 | 3.6474 | 1200 | 0.7329 | 0.5896 |
0.117 | 4.2553 | 1400 | 0.7819 | 0.5211 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0
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openai/whisper-medium