whisper-3000ms-v2 / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-tiny-akan
    results: []

whisper-tiny-akan

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: 1.1467
  • Wer: 45.0456

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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5414 10.0 250 0.7596 55.6922
0.09 20.0 500 0.9048 52.3362
0.0275 30.0 750 1.0300 49.0091
0.0114 40.0 1000 1.0959 47.4902
0.004 50.0 1250 1.1247 45.3783
0.0017 60.0 1500 1.1412 45.3493
0.0009 70.0 1750 1.1437 44.6261
0.0007 80.0 2000 1.1467 45.0456

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1