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Saugatkafley/
distilbert-Nepali-NER

Name: distilbert-Nepali-NER
Rating: 2.5 (9 reviews)

generated_from_trainer

distilbert/distilbert-base-uncased

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distilbert-Nepali-NER

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2917
Precision: 0.0843
Recall: 0.0538
F1: 0.0657
Accuracy: 0.9259

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: 64
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Accuracy	F1	Validation Loss	Precision	Recall
No log	0.92	200	0.8685	0.0	0.4700	0.0	0.0
No log	1.84	400	0.8984	0.0135	0.3581	0.0556	0.0077
0.4549	2.76	600	0.9087	0.0361	0.3188	0.0833	0.0231
0.4549	3.69	800	0.9111	0.0460	0.3040	0.0909	0.0308
0.2088	4.61	1000	0.9173	0.0396	0.2972	0.0556	0.0308
0.2088	5.53	1200	0.3065	0.0721	0.0615	0.0664	0.9100
0.2088	6.45	1400	0.2924	0.1724	0.0769	0.1064	0.9212
0.1601	7.37	1600	0.2929	0.0745	0.0538	0.0625	0.9234
0.1601	8.29	1800	0.2903	0.0893	0.0385	0.0538	0.9257
0.1114	9.22	2000	0.2917	0.0843	0.0538	0.0657	0.9259

Framework versions

Transformers 4.39.1
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Saugatkafley/distilbert-Nepali-NER

distilbert-Nepali-NER

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Saugatkafley/
distilbert-Nepali-NER