Whisper base te - jayavardhan
This model is a fine-tuned version of openai/whisper-base on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.1934
- Wer: 70.4367
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_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: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.084 | 6.12 | 500 | 0.1455 | 71.1065 |
| 0.0297 | 12.23 | 1000 | 0.1682 | 69.8570 |
| 0.0175 | 18.35 | 1500 | 0.1934 | 70.4367 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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