README.md

metadata

library_name: transformers
language:
  - en
license: mit
base_model: lelapa/distill_whisper_call_center_en_merged
tags:
  - generated_from_trainer
datasets:
  - Luandrie/www_compliance_english_colab
metrics:
  - wer
model-index:
  - name: Distill Whisper Call Center Compliance
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: www_compliance_tforge
          type: Luandrie/www_compliance_english_colab
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 7.317073170731707

Distill Whisper Call Center Compliance

This model is a fine-tuned version of lelapa/distill_whisper_call_center_en_merged on the www_compliance_tforge dataset. It achieves the following results on the evaluation set:

• Loss: 0.4256
• Wer: 7.3171

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: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• 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: 25
• training_steps: 200
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0001	34.7826	100	0.4194	7.3171
0.0001	69.5652	200	0.4256	7.3171

Framework versions

• Transformers 4.45.2
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.20.3