w2v-bert-2.0-nepali-iteration-2 – AI Model by kiranpantha | AlphaNeural AI

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kiranpantha/
w2v-bert-2.0-nepali-iteration-2

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automatic-speech-recognition

generated_from_trainer

kiranpantha/OpenSLR54-Balanced-Nepali

kiranpantha/w2v-bert-2.0-nepali-iteration-test

endpoints_compatible

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Wave2Vec2-Bert2.0 - Kiran Pantha

This model is a fine-tuned version of kiranpantha/w2v-bert-2.0-nepali-iteration-test on the OpenSLR54 dataset. It achieves the following results on the evaluation set:

Loss: 0.4545
Wer: 0.4636

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.392	0.15	300	0.4561	0.4579
0.5077	0.3	600	0.5402	0.5145
0.5371	0.45	900	0.5083	0.4923
0.4943	0.6	1200	0.5103	0.5147
0.5049	0.75	1500	0.4811	0.4752
0.4809	0.9	1800	0.4751	0.4689
0.4633	1.05	2100	0.5031	0.4883
0.3843	1.2	2400	0.4703	0.4573
0.3753	1.35	2700	0.4542	0.4497
0.356	1.5	3000	0.4510	0.4503
0.3668	1.65	3300	0.4591	0.4524
0.3386	1.8	3600	0.4399	0.4459
0.3452	1.95	3900	0.4545	0.4636

Framework versions

Transformers 4.45.0.dev0
Pytorch 2.4.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1