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---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Sep29-Mixat-whisper-lg-3-transliteration-0.1trainasval
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. -->
# Sep29-Mixat-whisper-lg-3-transliteration-0.1trainasval
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: 0.7875
- Wer: 39.7972
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.7619 | 0.4762 | 100 | 0.5335 | 54.2752 |
| 0.4908 | 0.9524 | 200 | 0.4641 | 49.9738 |
| 0.3846 | 1.4286 | 300 | 0.4498 | 43.4342 |
| 0.389 | 1.9048 | 400 | 0.4382 | 42.3151 |
| 0.2851 | 2.3810 | 500 | 0.4605 | 42.1927 |
| 0.2723 | 2.8571 | 600 | 0.4651 | 42.0878 |
| 0.202 | 3.3333 | 700 | 0.4855 | 40.9862 |
| 0.1731 | 3.8095 | 800 | 0.4809 | 41.3184 |
| 0.1243 | 4.2857 | 900 | 0.5475 | 40.6540 |
| 0.0988 | 4.7619 | 1000 | 0.5303 | 40.7064 |
| 0.0742 | 5.2381 | 1100 | 0.5775 | 40.6889 |
| 0.0531 | 5.7143 | 1200 | 0.5825 | 40.5316 |
| 0.0482 | 6.1905 | 1300 | 0.5976 | 41.3534 |
| 0.0368 | 6.6667 | 1400 | 0.6118 | 41.0911 |
| 0.0312 | 7.1429 | 1500 | 0.6439 | 42.0353 |
| 0.0242 | 7.6190 | 1600 | 0.6332 | 42.0528 |
| 0.0239 | 8.0952 | 1700 | 0.6684 | 39.3251 |
| 0.018 | 8.5714 | 1800 | 0.6527 | 42.3326 |
| 0.019 | 9.0476 | 1900 | 0.6736 | 40.7239 |
| 0.0153 | 9.5238 | 2000 | 0.6701 | 42.3326 |
| 0.0168 | 10.0 | 2100 | 0.7033 | 43.6790 |
| 0.0134 | 10.4762 | 2200 | 0.7028 | 40.2868 |
| 0.0141 | 10.9524 | 2300 | 0.6997 | 43.9063 |
| 0.0112 | 11.4286 | 2400 | 0.7055 | 42.1927 |
| 0.0118 | 11.9048 | 2500 | 0.7112 | 40.4266 |
| 0.0091 | 12.3810 | 2600 | 0.7509 | 41.5982 |
| 0.0106 | 12.8571 | 2700 | 0.7075 | 42.7872 |
| 0.0072 | 13.3333 | 2800 | 0.7263 | 43.3992 |
| 0.0096 | 13.8095 | 2900 | 0.7365 | 42.5249 |
| 0.0086 | 14.2857 | 3000 | 0.7722 | 42.0353 |
| 0.0099 | 14.7619 | 3100 | 0.7480 | 40.9862 |
| 0.0112 | 15.2381 | 3200 | 0.7422 | 40.9512 |
| 0.0076 | 15.7143 | 3300 | 0.7749 | 41.3709 |
| 0.0087 | 16.1905 | 3400 | 0.7505 | 39.9545 |
| 0.0073 | 16.6667 | 3500 | 0.7583 | 41.8780 |
| 0.0072 | 17.1429 | 3600 | 0.7541 | 41.0911 |
| 0.0063 | 17.6190 | 3700 | 0.7516 | 40.9337 |
| 0.0074 | 18.0952 | 3800 | 0.7798 | 41.2135 |
| 0.0067 | 18.5714 | 3900 | 0.7780 | 40.4791 |
| 0.0078 | 19.0476 | 4000 | 0.7596 | 41.2660 |
| 0.0061 | 19.5238 | 4100 | 0.7660 | 39.6048 |
| 0.0071 | 20.0 | 4200 | 0.7699 | 40.9862 |
| 0.0045 | 20.4762 | 4300 | 0.7855 | 41.4583 |
| 0.0055 | 20.9524 | 4400 | 0.7875 | 39.7972 |
### Framework versions
- Transformers 4.43.4
- Pytorch 2.4.1
- Datasets 3.0.0
- Tokenizers 0.19.1
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