asr2_medium_v0.9 / README.md
miosipof's picture
End of training
53b3bbf verified
metadata
library_name: peft
language:
  - it
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - b-brave-clean
metrics:
  - wer
model-index:
  - name: Whisper Medium
    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: 41.833810888252145
            name: Wer

Whisper Medium

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

  • Loss: 0.6398
  • Wer: 41.8338
  • Cer: 30.4702
  • 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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • 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: 0.3
  • num_epochs: 12
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer Lr
3.6633 1.0 168 1.8570 149.4269 97.5309 0.0001
1.2316 2.0 336 0.9484 66.4756 45.5477 0.0002
0.8773 3.0 504 0.8240 117.3352 102.2590 0.0002
0.5747 4.0 672 0.7314 76.3610 56.0809 0.0003
0.3652 5.0 840 0.6545 104.1547 90.4124 0.0002
0.2632 6.0 1008 0.6305 50.5731 34.6467 0.0002
0.1568 7.0 1176 0.5926 90.1146 80.4833 0.0002
0.104 8.0 1344 0.6388 47.5645 33.4121 0.0001
0.0356 9.0 1512 0.6073 42.8367 46.9398 0.0001
0.0189 10.0 1680 0.6361 42.5501 47.1500 0.0001
0.0089 11.0 1848 0.6385 41.9771 30.4965 0.0000
0.0108 11.9313 2004 0.6398 41.8338 30.4702 0.0000

Framework versions

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