---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: whisper-base-ga2en-v1.0
  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-base-ga2en-v1.0

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5231
- Bleu: 19.21
- Chrf: 33.89
- Wer: 86.4025

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.03
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu  | Chrf  | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:-----:|:-----:|:--------:|
| 0.5607        | 1.48  | 100  | 2.0068          | 13.89 | 29.73 | 102.1612 |
| 0.2227        | 2.96  | 200  | 2.1047          | 19.02 | 32.6  | 83.8361  |
| 0.0613        | 4.44  | 300  | 2.2670          | 20.37 | 34.38 | 82.9806  |
| 0.0491        | 5.93  | 400  | 2.2766          | 18.72 | 35.07 | 84.4665  |
| 0.0292        | 7.41  | 500  | 2.3870          | 19.19 | 33.57 | 85.2769  |
| 0.0307        | 8.89  | 600  | 2.4211          | 17.65 | 33.18 | 89.8244  |
| 0.0195        | 10.37 | 700  | 2.4980          | 19.56 | 33.37 | 83.3859  |
| 0.0165        | 11.85 | 800  | 2.4975          | 19.03 | 33.53 | 85.3219  |
| 0.0113        | 13.33 | 900  | 2.5300          | 18.93 | 33.95 | 85.9072  |
| 0.0097        | 14.81 | 1000 | 2.5231          | 19.21 | 33.89 | 86.4025  |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2