This model is a fine-tuned version of arun100/whisper-base-bn on the mozilla-foundation/common_voice_16_0 bn dataset. It achieves the following results on the evaluation set:

Loss: 0.2671
Wer: 35.6026

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-06
train_batch_size: 32
eval_batch_size: 32
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: 50
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2423	1.72	500	0.2710	35.9570
0.2329	3.43	1000	0.2671	35.6026

Framework versions

Transformers 4.38.0.dev0
Pytorch 2.1.2+cu121
Datasets 2.16.2.dev0
Tokenizers 0.15.0

arun100/whisper-base-bn-4

Whisper Base Bengali

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

arun100/
whisper-base-bn-4