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whisper-tiny-1000-diverse-audios

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metadata
library_name: transformers
language:
  - spa
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Whisper Tiny 1000 Diverse Audios - vfranchis
    results: []

Whisper Tiny 1000 Diverse Audios - vfranchis

This model is a fine-tuned version of openai/whisper-tiny on the 1000 diverse audios 1.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1835
  • Wer: 42.9577

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 25
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.7684 0.4425 25 2.2485 135.5131
1.5347 0.8850 50 0.9286 75.5533
0.8425 1.3274 75 0.5561 56.4386
0.5722 1.7699 100 0.4103 43.4608
0.3867 2.2124 125 0.3423 40.5433
0.3107 2.6549 150 0.2967 51.0060
0.2931 3.0973 175 0.2656 78.8732
0.2031 3.5398 200 0.2421 57.8471
0.2004 3.9823 225 0.2305 51.8109
0.1254 4.4248 250 0.2198 22.4346
0.1332 4.8673 275 0.2070 22.2334
0.1089 5.3097 300 0.2049 51.4085
0.0627 5.7522 325 0.1988 28.5714
0.0959 6.1947 350 0.1948 31.6901
0.0794 6.6372 375 0.1910 28.8732
0.0696 7.0796 400 0.1879 43.5614
0.0458 7.5221 425 0.1861 43.4608
0.0524 7.9646 450 0.1841 53.5211
0.0453 8.4071 475 0.1832 40.4427
0.0485 8.8496 500 0.1835 42.9577

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1