Whisper Large V3 pl Fleurs Aug 2 - Chee Li
This model is a fine-tuned version of openai/whisper-large-v3 on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.1295
- Wer: 402.6139
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: 750
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0563 | 1.2579 | 1000 | 0.1102 | 448.8748 |
| 0.0144 | 2.5157 | 2000 | 0.1207 | 354.0117 |
| 0.0035 | 3.7736 | 3000 | 0.1205 | 514.6701 |
| 0.0009 | 5.0314 | 4000 | 0.1263 | 391.4104 |
| 0.0003 | 6.2893 | 5000 | 0.1280 | 385.1901 |
| 0.0001 | 7.5472 | 6000 | 0.1295 | 402.6139 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-large-v3