metadata

language:
  - pt
license: mit
base_model: RodrigoLimaRFL/distil-large-nurc-sp
tags:
  - generated_from_trainer
datasets:
  - sidleal/CORAA-MUPE-ASR-1
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: sidleal/CORAA-MUPE-ASR-1
          config: default
          split: validation
          args: 'split: test'
        metrics:
          - name: Wer
            type: wer
            value: 16.906779312781993

CORAA-MUPE-ASR distil-whisper fine-tuned

This model is a fine-tuned version of RodrigoLimaRFL/distil-large-nurc-sp on the CORAA-MUPE-ASR dataset. It achieves the following results on the evaluation set:

Loss: 0.3067
Wer: 16.9068

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: 18000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3322	0.1734	3000	0.3687	19.8514
0.3245	0.3467	6000	0.3466	18.9951
0.3021	0.5201	9000	0.3320	18.0409
0.2852	0.6934	12000	0.3220	18.0697
0.2819	0.8668	15000	0.3095	17.4081
0.2062	1.0402	18000	0.3067	16.9068

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1