whisper-tinyfinacialKI
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5532
- Wer: 62.9213
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: 1.35e-05
- train_batch_size: 8
- 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: 100
- training_steps: 1200
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
No log | 0.7519 | 100 | 0.7072 | 71.3483 |
No log | 1.5038 | 200 | 0.5276 | 51.1236 |
No log | 2.2556 | 300 | 0.4869 | 47.7528 |
No log | 3.0075 | 400 | 0.4923 | 43.8202 |
0.3216 | 3.7594 | 500 | 0.5228 | 57.3034 |
0.3216 | 4.5113 | 600 | 0.5561 | 52.8090 |
0.3216 | 5.2632 | 700 | 0.5168 | 55.6180 |
0.3216 | 6.0150 | 800 | 0.5289 | 64.0449 |
0.3216 | 6.7669 | 900 | 0.5541 | 57.3034 |
0.0049 | 7.5188 | 1000 | 0.5548 | 62.3596 |
0.0049 | 8.2707 | 1100 | 0.5499 | 63.4831 |
0.0049 | 9.0226 | 1200 | 0.5532 | 62.9213 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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