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whisper-large-v2-ft-tms-BTU6567_silence_base-on-car350-250422-v1
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.8963
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
13.985 | 1.0 | 1 | 14.5871 |
14.0198 | 2.0 | 2 | 14.5871 |
13.9792 | 3.0 | 3 | 14.5871 |
13.9951 | 4.0 | 4 | 14.5871 |
13.995 | 5.0 | 5 | 14.5871 |
14.0008 | 6.0 | 6 | 14.3061 |
13.7294 | 7.0 | 7 | 14.3061 |
13.7231 | 8.0 | 8 | 13.6134 |
13.0157 | 9.0 | 9 | 12.5096 |
11.682 | 10.0 | 10 | 10.4350 |
9.3305 | 11.0 | 11 | 7.3042 |
7.4152 | 12.0 | 12 | 6.3486 |
6.202 | 13.0 | 13 | 5.1358 |
5.0984 | 14.0 | 14 | 4.7347 |
4.8599 | 15.0 | 15 | 4.5979 |
4.7433 | 16.0 | 16 | 4.4747 |
4.6267 | 17.0 | 17 | 4.3350 |
4.4997 | 18.0 | 18 | 4.1838 |
4.3673 | 19.0 | 19 | 4.0262 |
4.2335 | 20.0 | 20 | 3.8706 |
4.0869 | 21.0 | 21 | 3.7173 |
3.9376 | 22.0 | 22 | 3.5768 |
3.7974 | 23.0 | 23 | 3.4486 |
3.674 | 24.0 | 24 | 3.3342 |
3.5471 | 25.0 | 25 | 3.2328 |
3.4338 | 26.0 | 26 | 3.1428 |
3.3387 | 27.0 | 27 | 3.0653 |
3.2617 | 28.0 | 28 | 2.9998 |
3.1746 | 29.0 | 29 | 2.9434 |
3.1137 | 30.0 | 30 | 2.8963 |
Framework versions
- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.0
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Model tree for dylanewbie/whisper-large-v2-ft-tms-BTU6567_silence_base-on-car350-250422-v1
Base model
openai/whisper-large-v2