README.md

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-large-v2-Bengali
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: bn
          split: test
          args: bn
        metrics:
          - name: Wer
            type: wer
            value: 12.51

openai/whisper-large-v2-Bengali

This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

• Loss:
• Wer: 12.51

Model description

This model was originally trained on Bengali data but evaluated on Assamese test split. Hence, tensorboard evaluation logs for Assamese are present. The model was later evaluated on Bengali test split.

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: 4
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• training_steps: 600

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0646	1.13	600		12.51

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu117
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2