whisper-small-dari – AI Model by latif98 | AlphaNeural AI

You can deploy this model and start earning money today!

latif98/
whisper-small-dari

like

0

automatic-speech-recognition

generated_from_trainer

openai/whisper-small

endpoints_compatible

Views

No views yet

whisper-small-dari

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

Loss: 0.3171
Wer: 30.1313

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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 128
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	1.0	7	0.6818	48.0304
3.2896	2.0	14	0.4796	38.9772
1.7258	3.0	21	0.3972	35.3836
1.7258	4.0	28	0.3604	32.1355
1.1070	5.0	35	0.3359	30.6151
0.8097	6.0	42	0.3274	31.2370
0.8097	7.0	49	0.3196	29.9931
0.6274	8.0	56	0.3194	29.9240
0.5292	9.0	63	0.3163	29.5784
0.4368	10.0	70	0.3171	30.1313

Framework versions

Transformers 5.14.1
Pytorch 2.10.0+cu128
Datasets 5.0.1
Tokenizers 0.22.2