README.md

metadata

library_name: transformers
language:
  - pmx
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - iitd-duk/paula
metrics:
  - wer
model-index:
  - name: Whisper-Small-paula
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Paula
          type: iitd-duk/paula
        metrics:
          - name: Wer
            type: wer
            value: 104.8076923076923

Whisper-Small-paula

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

• Loss: 3.1480
• Wer: 104.8077

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: 12
• eval_batch_size: 8
• 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: 100
• training_steps: 100
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.0443	5.0	100	3.1480	104.8077

Framework versions

• Transformers 4.46.0.dev0
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.20.1