metadata

language:
  - hi
license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
base_model: openai/whisper-tiny
datasets:
  - mozilla-foundation/common_voice_17_0
model-index:
  - name: Whisper tiny Hindi
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17.0
          type: mozilla-foundation/common_voice_17_0
          config: hi
          split: None
          args: 'config: hi, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 44.76572739187418

Whisper tiny Hindi

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.7189

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.001
train_batch_size: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.575	0.4484	100	0.8603
0.6631	0.8969	200	0.7189

Framework versions

PEFT 0.11.2.dev0
Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.19.3.dev0
Tokenizers 0.19.1