metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v2-medical-9
results: []
whisper-large-v2-medical-9
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: 0.1386
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-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.2381 | 20 | 0.5954 |
| 0.9678 | 0.4762 | 40 | 0.3312 |
| 0.372 | 0.7143 | 60 | 0.1767 |
| 0.1657 | 0.9524 | 80 | 0.1568 |
| 0.1297 | 1.1905 | 100 | 0.1507 |
| 0.1297 | 1.4286 | 120 | 0.1455 |
| 0.0923 | 1.6667 | 140 | 0.1403 |
| 0.0974 | 1.9048 | 160 | 0.1376 |
| 0.0753 | 2.1429 | 180 | 0.1389 |
| 0.053 | 2.3810 | 200 | 0.1396 |
| 0.053 | 2.6190 | 220 | 0.1384 |
| 0.0601 | 2.8571 | 240 | 0.1386 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.18.0
- Tokenizers 0.20.1