Whisper medium AT
This model is a fine-tuned version of openai/whisper-medium on the AT_ENT dataset. It achieves the following results on the evaluation set:
- Loss: 1.2100
- Wer: 66.8297
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 1.0 | 111 | 1.0527 | 63.9374 |
| No log | 2.0 | 222 | 1.0961 | 65.8796 |
| No log | 3.0 | 333 | 1.1626 | 67.5283 |
| No log | 4.0 | 444 | 1.2100 | 66.8297 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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Model tree for Rziane/whisper-medium-aeb_ENT
Base model
openai/whisper-medium