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metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: torgo_tiny_finetune_F03
    results: []

torgo_tiny_finetune_F03

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

  • Loss: 0.0640
  • Wer: 15.0892

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: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Wer
0.6368 0.85 500 0.1136 7.8189
0.11 1.69 1000 0.0872 9.1907
0.0969 2.54 1500 0.0843 9.3278
0.0679 3.39 2000 0.0980 7.1331
0.053 4.24 2500 0.0756 7.1331
0.0361 5.08 3000 0.0637 9.1907
0.0278 5.93 3500 0.0491 8.3676
0.0233 6.78 4000 0.0446 27.8464
0.0148 7.63 4500 0.0403 12.8944
0.0149 8.47 5000 0.0748 28.6694
0.0105 9.32 5500 0.0631 17.6955
0.0087 10.17 6000 0.0619 12.0713
0.0075 11.02 6500 0.0525 18.6557
0.004 11.86 7000 0.0588 19.7531
0.0039 12.71 7500 0.0618 24.5542
0.0029 13.56 8000 0.0915 13.7174
0.0022 14.41 8500 0.0638 20.4390
0.0013 15.25 9000 0.0946 14.5405
0.0004 16.1 9500 0.0746 15.7750
0.0003 16.95 10000 0.0633 11.2483
0.0001 17.8 10500 0.0645 12.7572
0.0001 18.64 11000 0.0631 14.4033
0.0001 19.49 11500 0.0640 15.0892

Framework versions

  • Transformers 4.32.0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.7
  • Tokenizers 0.13.3