README.md

metadata

library_name: peft
language:
  - it
base_model: b-brave/asr_double_training_15-10-2024_merged
tags:
  - generated_from_trainer
datasets:
  - ASR_BB_and_EC
metrics:
  - wer
model-index:
  - name: Whisper Medium
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: ASR_BB_and_EC
          type: ASR_BB_and_EC
          config: default
          split: test
          args: default
        metrics:
          - type: wer
            value: 35.5638166047088
            name: Wer

Whisper Medium

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

• Loss: 0.4733
• Wer: 35.5638

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-06
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant
• lr_scheduler_warmup_steps: 10
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.3876	0.9852	100	0.4835	36.3073
1.3282	1.9704	200	0.4776	36.1834
1.2853	2.9557	300	0.4733	35.5638

Framework versions

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