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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