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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-no-ag
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-no-ag
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: 0.0365
- Wer: 26.0523
## 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: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.7935 | 1.4317 | 100 | 0.1805 | 33.4471 |
| 0.164 | 2.8633 | 200 | 0.0531 | 18.6576 |
| 0.0556 | 4.2878 | 300 | 0.1691 | 21.3879 |
| 0.0531 | 5.7194 | 400 | 0.0423 | 26.6212 |
| 0.023 | 7.1439 | 500 | 0.1101 | 70.6485 |
| 0.027 | 8.5755 | 600 | 0.0749 | 25.3697 |
| 0.0092 | 10.0 | 700 | 0.0406 | 18.9989 |
| 0.0046 | 11.4317 | 800 | 0.0673 | 36.9738 |
| 0.0063 | 12.8633 | 900 | 0.0371 | 24.6871 |
| 0.0032 | 14.2878 | 1000 | 0.0428 | 27.1900 |
| 0.001 | 15.7194 | 1100 | 0.0536 | 27.3038 |
| 0.0001 | 17.1439 | 1200 | 0.0453 | 25.8248 |
| 0.0 | 18.5755 | 1300 | 0.0434 | 25.7110 |
| 0.0008 | 20.0 | 1400 | 0.0368 | 26.1661 |
| 0.0 | 21.4317 | 1500 | 0.0365 | 26.1661 |
| 0.0 | 22.8633 | 1600 | 0.0365 | 26.1661 |
| 0.0 | 24.2878 | 1700 | 0.0365 | 26.0523 |
| 0.0 | 25.7194 | 1800 | 0.0365 | 26.0523 |
| 0.0 | 27.1439 | 1900 | 0.0365 | 26.0523 |
| 0.0 | 28.5755 | 2000 | 0.0365 | 26.0523 |
### Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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