whisper-large-ver2 / README.md
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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-large-v2
model-index:
- name: whisper-large-ver2
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-large-ver2
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4756
- Cer: 11.2426
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0327 | 5.59 | 1000 | 0.3779 | 14.1439 |
| 0.004 | 11.17 | 2000 | 0.4122 | 13.6476 |
| 0.0005 | 16.76 | 3000 | 0.4584 | 11.2044 |
| 0.0004 | 22.35 | 4000 | 0.4756 | 11.2426 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2