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---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Sep26-Mixat-whisper-lg-3-transcript
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. -->
# Sep26-Mixat-whisper-lg-3-transcript
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7722
- Wer: 40.9156
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7871 | 0.4292 | 100 | 0.4161 | 34.9906 |
| 0.4974 | 0.8584 | 200 | 0.4319 | 33.8051 |
| 0.3796 | 1.2876 | 300 | 0.4348 | 39.1582 |
| 0.3711 | 1.7167 | 400 | 0.4504 | 38.4566 |
| 0.3527 | 2.1459 | 500 | 0.4676 | 41.7834 |
| 0.2699 | 2.5751 | 600 | 0.4600 | 37.4643 |
| 0.275 | 3.0043 | 700 | 0.4449 | 37.8945 |
| 0.1566 | 3.4335 | 800 | 0.5121 | 40.7568 |
| 0.1658 | 3.8627 | 900 | 0.5067 | 40.8252 |
| 0.1125 | 4.2918 | 1000 | 0.5469 | 41.1772 |
| 0.0913 | 4.7210 | 1100 | 0.5818 | 40.3803 |
| 0.0806 | 5.1502 | 1200 | 0.6051 | 41.2041 |
| 0.0519 | 5.5794 | 1300 | 0.5997 | 40.6908 |
| 0.0545 | 6.0086 | 1400 | 0.6158 | 41.0574 |
| 0.0323 | 6.4378 | 1500 | 0.6482 | 40.7617 |
| 0.034 | 6.8670 | 1600 | 0.6761 | 39.0140 |
| 0.0259 | 7.2961 | 1700 | 0.7324 | 42.2796 |
| 0.0249 | 7.7253 | 1800 | 0.7128 | 41.8616 |
| 0.021 | 8.1545 | 1900 | 0.7722 | 40.9156 |
### Framework versions
- Transformers 4.43.4
- Pytorch 2.4.1
- Datasets 3.0.0
- Tokenizers 0.19.1
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