metadata
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-LoRA_both
results: []
whisper-medium-LoRA_both
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1915
- Wer: 8.5302
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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3833 | 1.0 | 1385 | 0.2992 | 13.2344 |
| 0.2438 | 2.0 | 2770 | 0.2508 | 14.7960 |
| 0.1811 | 3.0 | 4155 | 0.2108 | 9.0182 |
| 0.1208 | 4.0 | 5540 | 0.1966 | 9.1548 |
| 0.064 | 5.0 | 6925 | 0.1958 | 8.4326 |
| 0.0227 | 6.0 | 8310 | 0.1915 | 8.5302 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3