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metadata
library_name: peft
language:
  - it
base_model: b-brave/asr_double_training_15-10-2024_merged
tags:
  - generated_from_trainer
datasets:
  - b-brave/speech_disorders_voice_edit
metrics:
  - wer
model-index:
  - name: Whisper Medium
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: b-brave/speech_disorders_voice_edit
          type: b-brave/speech_disorders_voice_edit
          config: default
          split: test
          args: default
        metrics:
          - type: wer
            value: 35.687732342007436
            name: Wer

Whisper Medium

This model is a fine-tuned version of b-brave/asr_double_training_15-10-2024_merged on the b-brave/speech_disorders_voice_edit dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4710
  • Wer: 35.6877

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: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 150
  • num_epochs: 8
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1179 1.3245 100 0.4789 35.8116
0.1085 2.6490 200 0.4765 36.6791
0.1207 3.9735 300 0.4743 36.8030
0.1101 5.2980 400 0.4723 35.9356
0.1 6.6225 500 0.4714 35.6877
0.1133 7.9470 600 0.4710 35.6877

Framework versions

  • PEFT 0.13.2
  • Transformers 4.45.2
  • Pytorch 2.2.0
  • Datasets 3.1.0
  • Tokenizers 0.20.3