ASR-small
This model is a fine-tuned version of openai/whisper-small on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 2.2485
- Wer: 0.5698
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: 0.0005
- train_batch_size: 16
- 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: 300
- training_steps: 2000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.3412 | 0.5 | 1000 | 2.5398 | 0.7801 |
0.6222 | 1.46 | 2000 | 2.2485 | 0.5698 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3
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Model tree for saif-daoud/ASR-small
Base model
openai/whisper-small