whisper-a-nomi-ls / 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-nomi-ls
    results: []

whisper-a-nomi-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: 0.0301
  • Wer: 97.3190

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 88 0.2173 32.7078
0.9256 2.0 176 0.0358 13.6729
0.1103 3.0 264 0.1075 45.6658
0.0399 4.0 352 0.0939 68.9008
0.0319 5.0 440 0.0241 19.1242
0.0144 6.0 528 0.0252 18.2306
0.01 7.0 616 0.0300 99.3744
0.0023 8.0 704 0.0268 97.9446
0.0023 9.0 792 0.0301 97.3190
0.0003 10.0 880 0.0301 97.3190
0.0 11.0 968 0.0301 97.3190

Framework versions

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