metadata

library_name: transformers
language:
  - mr
license: apache-2.0
base_model: Viraj008/whisper-small-mr_v4
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
  - fsicoli/common_voice_19_0
  - ylacombe/google-marathi
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Small MR v5 - Viraj Patil
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: 'Common Voice 17.0, google/fleurs '
          type: mozilla-foundation/common_voice_17_0
          config: mr
          split: None
          args: 'config: mr, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 34.12423353772328

Whisper Small MR v5 - Viraj Patil

This model is a fine-tuned version of Viraj008/whisper-small-mr_v4 on the Common Voice 17.0, google/fleurs dataset. It achieves the following results on the evaluation set:

Loss: 0.2496
Wer: 34.1242

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0573	0.5355	1000	0.2405	36.3370
0.0314	1.0710	2000	0.2484	35.4172
0.0298	1.6064	3000	0.2410	35.1640
0.0182	2.1419	4000	0.2496	34.1242

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0