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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ap-jLype7eJniXiXbhFmRXQx3
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. -->
# ap-jLype7eJniXiXbhFmRXQx3
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4775
- Model Preparation Time: 0.0215
- Wer: 0.1259
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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: 400
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|:------:|
| 0.4643 | 0.9791 | 41 | 0.4187 | 0.0215 | 0.1415 |
| 0.2421 | 1.9791 | 82 | 0.3216 | 0.0215 | 0.1133 |
| 0.1917 | 2.9791 | 123 | 0.3110 | 0.0215 | 0.1113 |
| 0.1372 | 3.9791 | 164 | 0.3263 | 0.0215 | 0.1222 |
| 0.0873 | 4.9791 | 205 | 0.3568 | 0.0215 | 0.1108 |
| 0.0598 | 5.9791 | 246 | 0.3809 | 0.0215 | 0.1172 |
| 0.0323 | 6.9791 | 287 | 0.4263 | 0.0215 | 0.1150 |
| 0.0284 | 7.9791 | 328 | 0.4463 | 0.0215 | 0.1448 |
| 0.0149 | 8.9791 | 369 | 0.4452 | 0.0215 | 0.1219 |
| 0.0131 | 9.9791 | 410 | 0.4775 | 0.0215 | 0.1259 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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