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---
language:
- hre
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- ntviet/Hre-audio-dataset4
model-index:
- name: Whisper Small Hre 4.4 - male and female voice - 1000 steps,  metric CER, skip_special_tokens
    False
  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 Small Hre 4.4 - male and female voice - 1000 steps,  metric CER, skip_special_tokens False

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Hre audio dataset 4 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0208
- Cer Ortho: 0.0214
- Cer: 1.0204

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer Ortho | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.013         | 4.13  | 1000 | 0.0208          | 0.0214    | 1.0204 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2