Whisper base Hi - Sanchit Gandhi
This model is a fine-tuned version of openai/whisper-base on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1381
- Cer: 8.5165
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.3106 | 0.87 | 1000 | 0.3352 | 16.9784 |
| 0.1609 | 1.74 | 2000 | 0.1887 | 10.5303 |
| 0.0889 | 2.6 | 3000 | 0.1510 | 9.2926 |
| 0.0596 | 3.47 | 4000 | 0.1381 | 8.5165 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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Base model
openai/whisper-base