README.md

metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-small.en
tags:
  - generated_from_trainer
datasets:
  - bika5/pfedrax
metrics:
  - wer
model-index:
  - name: Whisper pfe - bika5
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: pfedrax
          type: bika5/pfedrax
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 92.92035398230088

Whisper pfe - bika5

This model is a fine-tuned version of openai/whisper-small.en on the pfedrax dataset. It achieves the following results on the evaluation set:

• Loss: 3.6101
• Model Preparation Time: 0.006
• Wer: 92.9204

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: 2000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Wer
0.0001	83.3333	1000	3.5216	0.006	92.9204
0.0	166.6667	2000	3.6101	0.006	92.9204

Framework versions

• Transformers 4.43.0.dev0
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1