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whisper-nm-no-ls

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-nm-no-ls
    results: []

whisper-nm-no-ls

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: 0.1565
  • Wer: 11.1562

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: 11
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 1.0 33 0.1768 8.9249
No log 2.0 66 0.2439 20.8925
No log 3.0 99 0.4285 255.7809
1.2232 4.0 132 0.2449 26.3692
1.2232 5.0 165 0.5282 37.9310
1.2232 6.0 198 0.2170 25.3550
0.3525 7.0 231 0.1980 74.4422
0.3525 8.0 264 0.1585 14.6045
0.3525 9.0 297 0.1963 18.0527
0.0919 10.0 330 0.1787 12.9817
0.0919 11.0 363 0.1565 11.1562

Framework versions

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