asr2_medium_v0.3 / README.md
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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: 57.44985673352435
            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: 0.6278
  • Wer: 57.4499
  • Cer: 38.7444
  • 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: 3e-05
  • 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: 0.5
  • num_epochs: 16
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer Lr
4.3003 1.0 251 1.8420 77.7937 47.7279 0.0000
2.9936 2.0 502 1.2434 77.3639 47.9117 0.0000
2.8135 3.0 753 1.1431 74.9284 47.7279 0.0000
2.4032 4.0 1004 1.0400 74.6418 47.1237 0.0000
1.9765 5.0 1255 0.9656 74.2120 47.2551 0.0000
1.8144 6.0 1506 0.8685 107.3066 74.4944 0.0000
1.4479 7.0 1757 0.8158 63.8968 42.3431 0.0000
1.2718 8.0 2008 0.7787 67.1920 45.3901 0.0000
1.135 9.0 2259 0.7262 111.1748 98.4502 0.0000
0.833 10.0 2510 0.7015 94.4126 61.3869 0.0000
0.7509 11.0 2761 0.6963 62.1777 41.7914 0.0000
0.7171 12.0 3012 0.6650 61.8911 42.9997 0.0000
0.4706 13.0 3263 0.6258 77.6504 57.8671 0.0000
0.4988 14.0 3514 0.6249 59.5989 40.5306 0.0000
0.4503 15.0 3765 0.6201 59.1691 40.0841 0.0000
0.3741 16.0 4016 0.6278 57.4499 38.7444 0.0000

Framework versions

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