README.md

metadata

language:
  - te
license: apache-2.0
base_model: openai/whisper-base
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_0
metrics:
  - wer
model-index:
  - name: Breeze DSW Telugu - base
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_16_0 te
          type: mozilla-foundation/common_voice_16_0
          config: te
          split: test
          args: te
        metrics:
          - name: Wer
            type: wer
            value: 89.28571428571429

Breeze DSW Telugu - base

This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 te dataset. It achieves the following results on the evaluation set:

• Loss: 2.0469
• Wer: 89.2857

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: 32
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 2000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0007	99.0	200	2.0469	89.2857
0.0002	199.0	400	2.2441	90.6593

Framework versions

• Transformers 4.37.0.dev0
• Pytorch 2.1.2+cu121
• Datasets 2.16.2.dev0
• Tokenizers 0.15.0