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---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./3479
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. -->
# ./3479
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the 3479 clips dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5117
- Wer Ortho: 27.4535
- Wer: 19.3463
## 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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- 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: 200
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.8906 | 0.5109 | 100 | 0.6318 | 33.6218 | 25.1010 |
| 0.6428 | 1.0217 | 200 | 0.5620 | 30.8415 | 22.5971 |
| 0.5279 | 1.5326 | 300 | 0.5435 | 32.0107 | 23.8886 |
| 0.4958 | 2.0434 | 400 | 0.5244 | 30.0037 | 21.7800 |
| 0.4238 | 2.5543 | 500 | 0.5171 | 28.4662 | 20.2337 |
| 0.4016 | 3.0651 | 600 | 0.5132 | 28.0980 | 19.8647 |
| 0.3562 | 3.5760 | 700 | 0.5132 | 27.6100 | 19.7505 |
| 0.3467 | 4.0868 | 800 | 0.5103 | 27.1037 | 19.0828 |
| 0.308 | 4.5977 | 900 | 0.5117 | 27.3246 | 19.1618 |
| 0.3174 | 5.1086 | 1000 | 0.5117 | 27.4535 | 19.3463 |
### Framework versions
- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.21.0
- Tokenizers 0.19.1
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