metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-fine-tuned
results: []
whisper-fine-tuned
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.1515
- Wer: 1.0004
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.1863 | 1.6393 | 500 | 3.5257 | 0.9991 |
| 1.4263 | 3.2787 | 1000 | 4.2011 | 1.0383 |
| 1.1951 | 4.9180 | 1500 | 4.1093 | 0.9934 |
| 0.8698 | 6.5574 | 2000 | 4.3517 | 1.7507 |
| 0.7181 | 8.1967 | 2500 | 4.5794 | 1.2076 |
| 0.718 | 9.8361 | 3000 | 4.6911 | 1.2960 |
| 0.5776 | 11.4754 | 3500 | 4.8927 | 1.0814 |
| 0.624 | 13.1148 | 4000 | 4.9520 | 1.1319 |
| 0.5781 | 14.7541 | 4500 | 5.0590 | 0.9934 |
| 0.5189 | 16.3934 | 5000 | 5.1515 | 1.0004 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0