WhisperForNamedEntityRecognition
This model is a fine-tuned version of openai/whisper-small on the qmeeus/slue-voxpopuli dataset. It achieves the following results on the evaluation set:
- Loss: 8.1514
- Wer: 10.4828
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 1600
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 31.3741 | 0.06 | 100 | 25.8582 | 10.4828 |
| 13.0078 | 1.03 | 200 | 13.4173 | 10.4828 |
| 10.3619 | 1.09 | 300 | 10.8540 | 10.4828 |
| 8.7869 | 2.06 | 400 | 9.6249 | 10.4828 |
| 7.3964 | 3.02 | 500 | 9.1812 | 10.4828 |
| 6.6321 | 3.08 | 600 | 8.6536 | 10.4828 |
| 6.4612 | 4.05 | 700 | 8.6046 | 10.4828 |
| 4.8358 | 5.02 | 800 | 8.0890 | 10.4828 |
| 4.4918 | 5.08 | 900 | 8.3141 | 10.4828 |
| 4.7548 | 6.04 | 1000 | 8.1660 | 10.4828 |
| 3.7881 | 7.01 | 1100 | 8.2471 | 10.4828 |
| 3.1916 | 7.07 | 1200 | 8.0779 | 10.4828 |
| 3.2039 | 8.04 | 1300 | 8.1106 | 10.4828 |
| 3.038 | 9.0 | 1400 | 8.0875 | 10.4828 |
| 2.3249 | 9.07 | 1500 | 8.1025 | 10.4828 |
| 2.6124 | 10.03 | 1600 | 8.1514 | 10.4828 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.10.0
- Datasets 2.7.1.dev0
- Tokenizers 0.11.0
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