whisper-small-hyper-tuned-v3
This model is a fine-tuned version of Sekiraw/whisper-small-hyper-tuned-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2305
- Wer: 0.3964
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-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: 1000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1243 | 0.0330 | 100 | 0.2124 | 0.3780 |
0.1045 | 0.0660 | 200 | 0.2246 | 0.3971 |
0.0936 | 0.0990 | 300 | 0.2496 | 0.4044 |
0.0883 | 0.1320 | 400 | 0.2906 | 0.4809 |
0.0964 | 0.1650 | 500 | 0.3260 | 0.4525 |
0.0974 | 0.1980 | 600 | 0.3168 | 0.4578 |
4.0232 | 0.2309 | 700 | 3.4281 | 1.0 |
2.0352 | 0.2639 | 800 | 0.3124 | 0.4796 |
0.1273 | 0.2969 | 900 | 0.2447 | 0.4228 |
0.1489 | 0.3299 | 1000 | 0.2305 | 0.3964 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.1.0+cu118
- Datasets 3.0.1
- Tokenizers 0.20.0
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Model tree for Sekiraw/whisper-small-hyper-tuned-v3
Base model
openai/whisper-small
Finetuned
Sekiraw/whisper-small-hyper-tuned-v2