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metadata
language:
  - as
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: openai/whisper-small-Assamese
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: as
          split: test
          args: as
        metrics:
          - name: Wer
            type: wer
            value: 32.01588160981772

openai/whisper-small-Assamese

This model is a fine-tuned version of kpriyanshu256/whisper-small-as-500-64-1e-05-bn on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5071
  • Wer: 32.0159

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: 8
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss Wer
0.0658 8.01 100 0.3295 31.9978
0.0027 16.02 200 0.4516 31.8896
0.0005 24.02 300 0.4881 31.9256
0.0003 33.01 400 0.5026 31.9437
0.0003 41.02 500 0.5071 32.0159

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1