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whisper-small-mar

Automatic Speech Recognition
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whisper
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metadata
library_name: transformers
language:
  - mar
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Whisper_Small_mar
    results: []

Whisper_Small_mar

This model is a fine-tuned version of openai/whisper-small on the openslr dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1866
  • Wer: 26.4000

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: 16
  • seed: 42
  • 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: 50
  • training_steps: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.2222 10 0.5078 64.3733
No log 0.4444 20 0.2853 37.3333
0.5228 0.6667 30 0.2131 30.3467
0.5228 0.8889 40 0.2020 32.64
0.183 1.1111 50 0.1866 26.4000

Framework versions

  • Transformers 4.49.0
  • Pytorch 2.6.0+cu124
  • Datasets 3.3.2
  • Tokenizers 0.21.0