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

sgangireddy/whisper-small-ta

Whisper Small Tamil FLEURS