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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-a-clp-ls-35
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-a-clp-ls-35
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: 0.0283
- Wer: 7.3375
## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 132
- num_epochs: 35
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log | 1.0 | 40 | 0.1519 | 181.5514 |
| No log | 2.0 | 80 | 0.1651 | 50.5241 |
| 1.2204 | 3.0 | 120 | 0.3615 | 112.1593 |
| 1.2204 | 4.0 | 160 | 0.3251 | 62.8931 |
| 0.1484 | 5.0 | 200 | 0.2501 | 50.3145 |
| 0.1484 | 6.0 | 240 | 0.1648 | 61.2159 |
| 0.1484 | 7.0 | 280 | 0.1351 | 30.8176 |
| 0.0823 | 8.0 | 320 | 0.0712 | 30.1887 |
| 0.0823 | 9.0 | 360 | 0.1608 | 57.0231 |
| 0.0528 | 10.0 | 400 | 0.0652 | 21.5933 |
| 0.0528 | 11.0 | 440 | 0.0569 | 19.9161 |
| 0.0528 | 12.0 | 480 | 0.0706 | 22.6415 |
| 0.0436 | 13.0 | 520 | 0.0498 | 14.6751 |
| 0.0436 | 14.0 | 560 | 0.0493 | 22.4319 |
| 0.0374 | 15.0 | 600 | 0.0946 | 28.0922 |
| 0.0374 | 16.0 | 640 | 0.0930 | 29.5597 |
| 0.0374 | 17.0 | 680 | 0.0532 | 24.3187 |
| 0.0249 | 18.0 | 720 | 0.0639 | 22.2222 |
| 0.0249 | 19.0 | 760 | 0.0355 | 11.3208 |
| 0.0151 | 20.0 | 800 | 0.0608 | 14.2558 |
| 0.0151 | 21.0 | 840 | 0.0612 | 15.7233 |
| 0.0151 | 22.0 | 880 | 0.0632 | 13.8365 |
| 0.0124 | 23.0 | 920 | 0.0436 | 15.3040 |
| 0.0124 | 24.0 | 960 | 0.0415 | 14.4654 |
| 0.0084 | 25.0 | 1000 | 0.0474 | 17.6101 |
| 0.0084 | 26.0 | 1040 | 0.0284 | 10.2725 |
| 0.0084 | 27.0 | 1080 | 0.0291 | 7.9665 |
| 0.0058 | 28.0 | 1120 | 0.0275 | 7.9665 |
| 0.0058 | 29.0 | 1160 | 0.0302 | 7.9665 |
| 0.005 | 30.0 | 1200 | 0.0278 | 7.9665 |
| 0.005 | 31.0 | 1240 | 0.0277 | 8.1761 |
| 0.005 | 32.0 | 1280 | 0.0289 | 8.1761 |
| 0.0035 | 33.0 | 1320 | 0.0284 | 7.3375 |
| 0.0035 | 34.0 | 1360 | 0.0283 | 7.3375 |
| 0.0035 | 34.1266 | 1365 | 0.0283 | 7.3375 |
### Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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