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---
language:
- pt
license: mit
base_model: RodrigoLimaRFL/distil-whisper-nurc-sp-fine-tuned
tags:
- generated_from_trainer
datasets:
- nilc-nlp/CORAA-MUPE-ASR
metrics:
- wer
model-index:
- name: CORAA-MUPE-ASR distil-whisper fine-tuned
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: CORAA-MUPE-ASR
type: nilc-nlp/CORAA-MUPE-ASR
config: default
split: test
args: 'split: test'
metrics:
- name: Wer
type: wer
value: 15.273584751709397
---
<!-- 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. -->
# CORAA-MUPE-ASR distil-whisper fine-tuned
This model is a fine-tuned version of [RodrigoLimaRFL/distil-whisper-nurc-sp-fine-tuned](https://huggingface.co./RodrigoLimaRFL/distil-whisper-nurc-sp-fine-tuned) on the CORAA-MUPE-ASR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3488
- Wer: 15.2736
## 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: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4451 | 0.0558 | 1000 | 0.4482 | 18.5598 |
| 0.4006 | 0.1116 | 2000 | 0.4095 | 17.3061 |
| 0.2992 | 0.1674 | 3000 | 0.3848 | 16.5660 |
| 0.2781 | 0.2232 | 4000 | 0.3609 | 15.5857 |
| 0.2839 | 0.2790 | 5000 | 0.3488 | 15.2736 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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