whisper-large-stt4sg
This model is a fine-tuned version of openai/whisper-large-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2355
- Wer: 15.5402
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: 5e-06
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2994 | 0.0801 | 1000 | 0.3001 | 19.6658 |
| 0.2953 | 0.1602 | 2000 | 0.2741 | 18.0230 |
| 0.2638 | 0.2403 | 3000 | 0.2575 | 17.0951 |
| 0.2456 | 0.3205 | 4000 | 0.2421 | 15.9823 |
| 0.2442 | 0.4006 | 5000 | 0.2355 | 15.5402 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-large-v2