metadata
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-finetuned-7
results: []
whisper-large-v3-finetuned-7
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: 1.2896
- Wer: 19.3061
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: 2e-09
- 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 |
|---|---|---|---|---|
| 0.9515 | 1.0 | 7532 | 1.7699 | 27.1166 |
| 1.2475 | 2.0 | 15064 | 1.6434 | 24.6623 |
| 1.2258 | 3.0 | 22596 | 1.5462 | 22.7052 |
| 0.4176 | 4.0 | 30128 | 1.4713 | 21.4012 |
| 1.2809 | 5.0 | 37660 | 1.4125 | 20.3966 |
| 1.5466 | 6.0 | 45192 | 1.3656 | 19.7720 |
| 0.6952 | 7.0 | 52724 | 1.3283 | 19.4675 |
| 2.0103 | 8.0 | 60256 | 1.3030 | 19.3087 |
| 1.4738 | 9.0 | 67788 | 1.2914 | 19.3087 |
| 3.545 | 10.0 | 75320 | 1.2896 | 19.3061 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2