./7326
This model is a fine-tuned version of openai/whisper-large-v3 on the 7326 FULL-2024-10-24 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3911
- Wer Ortho: 22.6474
- Wer: 15.5576
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: 3e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 1600
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
0.686 | 0.4851 | 200 | 0.4602 | 26.0150 | 18.7885 |
0.5255 | 0.9703 | 400 | 0.4216 | 24.3312 | 17.1358 |
0.4328 | 1.4554 | 600 | 0.4028 | 23.2291 | 15.9895 |
0.4064 | 1.9406 | 800 | 0.3945 | 23.2291 | 16.1897 |
0.3579 | 2.4257 | 1000 | 0.3945 | 22.8195 | 15.7618 |
0.3409 | 2.9109 | 1200 | 0.3894 | 22.6884 | 15.5812 |
0.3131 | 3.3960 | 1400 | 0.3909 | 22.6556 | 15.6008 |
0.3021 | 3.8811 | 1600 | 0.3911 | 22.6474 | 15.5576 |
Framework versions
- Transformers 4.45.1
- Pytorch 1.13.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.0
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Base model
openai/whisper-large-v3