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whisper-a-no-ag

Automatic Speech Recognition
Transformers
Safetensors
whisper
Generated from Trainer
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metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-a-no-ag
    results: []

whisper-a-no-ag

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0365
  • Wer: 26.0523

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: 0.0004
  • 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_steps: 132
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.7935 1.4317 100 0.1805 33.4471
0.164 2.8633 200 0.0531 18.6576
0.0556 4.2878 300 0.1691 21.3879
0.0531 5.7194 400 0.0423 26.6212
0.023 7.1439 500 0.1101 70.6485
0.027 8.5755 600 0.0749 25.3697
0.0092 10.0 700 0.0406 18.9989
0.0046 11.4317 800 0.0673 36.9738
0.0063 12.8633 900 0.0371 24.6871
0.0032 14.2878 1000 0.0428 27.1900
0.001 15.7194 1100 0.0536 27.3038
0.0001 17.1439 1200 0.0453 25.8248
0.0 18.5755 1300 0.0434 25.7110
0.0008 20.0 1400 0.0368 26.1661
0.0 21.4317 1500 0.0365 26.1661
0.0 22.8633 1600 0.0365 26.1661
0.0 24.2878 1700 0.0365 26.0523
0.0 25.7194 1800 0.0365 26.0523
0.0 27.1439 1900 0.0365 26.0523
0.0 28.5755 2000 0.0365 26.0523

Framework versions

  • Transformers 4.47.0.dev0
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0