metadata

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

CORAA-MUPE-ASR distil-whisper fine-tuned

This model is a fine-tuned version of 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