metadata

language:
  - hi
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Hindi - Shripad Bhat
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: hi
          split: test
          args: hi
        metrics:
          - name: Wer
            type: wer
            value: 21.451908746990714
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: FLEURS
          type: google/fleurs
          config: hi_in
          split: test
          args: hi
        metrics:
          - name: Wer
            type: wer
            value: 22.11

Whisper Small Hindi - Shripad Bhat

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

Loss: 0.3909
Wer: 21.4519

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
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: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.4337	0.73	100	0.4874	47.5868
0.1894	1.47	200	0.3264	23.9482
0.1007	2.21	300	0.3101	22.5267
0.0984	2.94	400	0.3064	21.5723
0.0555	3.67	500	0.3325	22.0251
0.029	4.41	600	0.3439	21.4863
0.0163	5.15	700	0.3668	21.6468
0.0153	5.88	800	0.3756	21.4662
0.0081	6.62	900	0.3888	21.5035
0.0059	7.35	1000	0.3909	21.4519

Framework versions

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