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metadata
library_name: peft
language:
  - it
license: cc-by-nc-4.0
base_model: nyrahealth/CrisperWhisper
tags:
  - generated_from_trainer
datasets:
  - b-brave-clean
metrics:
  - wer
model-index:
  - name: Whisper-Crisper
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: b-brave-clean
          type: b-brave-clean
          config: default
          split: test
          args: default
        metrics:
          - type: wer
            value: 155.63816604708796
            name: Wer

Whisper-Crisper

This model is a fine-tuned version of nyrahealth/CrisperWhisper on the b-brave-clean dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2971
  • Wer: 155.6382
  • Cer: 74.4218
  • Lr: 0.0000

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: 0.0003
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.5
  • num_epochs: 8
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer Lr
1.0227 1.0 335 0.8979 601.9827 363.8095 0.0001
0.5552 2.0 670 0.5294 1520.4461 678.7302 0.0002
0.4207 3.0 1005 0.4611 403.5936 219.1610 0.0002
0.2025 4.0 1340 0.3812 346.8401 162.0408 0.0003
0.1216 5.0 1675 0.3001 400.3717 203.6054 0.0002
0.0478 6.0 2010 0.2932 198.6369 94.8299 0.0001
0.0313 7.0 2345 0.3033 241.0161 115.3288 0.0001
0.012 7.9776 2672 0.2971 155.6382 74.4218 0.0000

Framework versions

  • PEFT 0.14.0
  • Transformers 4.48.3
  • Pytorch 2.2.0
  • Datasets 3.2.0
  • Tokenizers 0.21.0