README.md

metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Small Tamil FLEURS
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs ta_in
          type: google/fleurs
          config: ta_in
          split: test
          args: ta_in
        metrics:
          - name: Wer
            type: wer
            value: 20.932719441556515

Whisper Small Tamil FLEURS

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

• Loss: 0.5390
• Wer: 20.9327

Model description

This model is fine-tuned for 1000 steps on Tamil Fluers data.

• Zero-shot - 35.2 (google/fluers test)
• fine-tune on FLUERS - 20.93 (google/fluers test) (-40%)

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
• gradient_accumulation_steps: 2
• 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: 500
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0004	83.33	1000	0.5390	20.9327

Framework versions

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