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WhispASR

Automatic Speech Recognition
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
base_model: openai/whisper-small
metrics:
  - wer
model-index:
  - name: checkpoints
    results: []
datasets:
  - ai4bharat/kathbath
language:
  - hi
pipeline_tag: automatic-speech-recognition

checkpoints

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: 1.0775
  • Wer: 54.4629

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: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1
  • training_steps: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.4636 0.0255 10 1.0775 54.4629

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1