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whisper-a-clp-ls-25

Automatic Speech Recognition
Transformers
Safetensors
whisper
Generated from Trainer
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whisper-a-clp-ls-25 / README.md
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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-clp-ls-25
    results: []

whisper-a-clp-ls-25

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: 0.0302
  • Wer: 8.3857

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 40 0.1805 27.4633
No log 2.0 80 0.2522 54.9266
1.2203 3.0 120 0.2866 59.5388
1.2203 4.0 160 0.1374 43.3962
0.1533 5.0 200 0.1516 46.1216
0.1533 6.0 240 0.1406 53.4591
0.1533 7.0 280 0.0704 17.8197
0.0561 8.0 320 0.0487 15.0943
0.0561 9.0 360 0.0395 11.7400
0.0225 10.0 400 0.0291 6.2893
0.0225 10.7342 429 0.0302 8.3857

Framework versions

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