metadata
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-finetuned-5
results: []
whisper-large-v3-finetuned-5
This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3599
- Wer: 50.9574
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: 1e-08
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.934 | 1.0 | 7532 | 0.9560 | 16.8450 |
0.8091 | 2.0 | 15064 | 0.5512 | 14.8480 |
1.8408 | 3.0 | 22596 | 0.4653 | 14.6010 |
0.1874 | 4.0 | 30128 | 0.4304 | 14.4735 |
0.0178 | 5.0 | 37660 | 0.3972 | 14.2372 |
1.2841 | 6.0 | 45192 | 0.3756 | 53.3820 |
0.0041 | 7.0 | 52724 | 0.3663 | 49.1462 |
0.3521 | 8.0 | 60256 | 0.3628 | 50.0624 |
0.0849 | 9.0 | 67788 | 0.3604 | 51.1061 |
1.2129 | 10.0 | 75320 | 0.3599 | 50.9574 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2