README.md

metadata

language:
  - tr
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - a
metrics:
  - wer
model-index:
  - name: Whisper large tr - Sanchit Gandhi
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: a
          type: a
          config: default
          split: test
          args: 'config: tr, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 100

Whisper large tr - Sanchit Gandhi

This model is a fine-tuned version of openai/whisper-large-v3 on the a dataset. It achieves the following results on the evaluation set:

• Loss: 5.1507
• Wer: 100.0

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: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.6231	1.0	2	5.4697	100.0
5.3829	2.0	4	5.1507	100.0

Framework versions

• Transformers 4.37.0.dev0
• Pytorch 2.1.0+cu121
• Datasets 2.16.0
• Tokenizers 0.15.0