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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium Fine Tuned 3000 Names SSD superU
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Medium Fine Tuned 3000 Names SSD superU
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1246
- Wer: 26.1364
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4987 | 0.2392 | 100 | 0.4556 | 51.7045 |
| 0.4092 | 0.4785 | 200 | 0.3531 | 48.5795 |
| 0.3696 | 0.7177 | 300 | 0.3179 | 48.0114 |
| 0.2694 | 0.9569 | 400 | 0.2911 | 38.6364 |
| 0.2162 | 1.1962 | 500 | 0.2809 | 36.6477 |
| 0.2378 | 1.4354 | 600 | 0.2682 | 34.9432 |
| 0.2057 | 1.6746 | 700 | 0.1950 | 28.9773 |
| 0.1681 | 1.9139 | 800 | 0.2118 | 36.3636 |
| 0.1217 | 2.1531 | 900 | 0.1847 | 26.9886 |
| 0.1235 | 2.3923 | 1000 | 0.1722 | 25.5682 |
| 0.1203 | 2.6316 | 1100 | 0.1655 | 26.7045 |
| 0.1182 | 2.8708 | 1200 | 0.1704 | 28.9773 |
| 0.062 | 3.1100 | 1300 | 0.1566 | 26.9886 |
| 0.0835 | 3.3493 | 1400 | 0.1455 | 23.8636 |
| 0.0738 | 3.5885 | 1500 | 0.1387 | 24.1477 |
| 0.0849 | 3.8278 | 1600 | 0.1354 | 25.0 |
| 0.0419 | 4.0670 | 1700 | 0.1298 | 24.4318 |
| 0.0512 | 4.3062 | 1800 | 0.1302 | 26.4205 |
| 0.0524 | 4.5455 | 1900 | 0.1251 | 26.4205 |
| 0.0411 | 4.7847 | 2000 | 0.1246 | 26.1364 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.2.2+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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