transformers safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-large-v2 license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-large-v2
metrics:
- wer
model-index:
- name: BA_Model_V3
  results: []
---

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# BA_Model_V3

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: 0.3495
- Wer: 21.1224
- Cer: 12.2080

## 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-06
- 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: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 1.0358        | 1.0   | 278  | 0.6770          | 23.3686 | 13.9275 |
| 0.2753        | 2.0   | 556  | 0.3313          | 20.7071 | 12.0535 |
| 0.2109        | 3.0   | 834  | 0.3098          | 20.7204 | 12.1752 |
| 0.1603        | 4.0   | 1112 | 0.3129          | 20.4645 | 11.8444 |
| 0.1224        | 5.0   | 1390 | 0.3242          | 20.8034 | 12.0535 |
| 0.0956        | 6.0   | 1668 | 0.3353          | 20.7802 | 11.9894 |
| 0.0781        | 7.0   | 1946 | 0.3464          | 21.0659 | 12.1725 |
| 0.0716        | 8.0   | 2224 | 0.3495          | 21.1224 | 12.2080 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
