my_awesome_wnut_model – AI Model by priyanshug0405 | AlphaNeural AI

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priyanshug0405/
my_awesome_wnut_model

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token-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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my_awesome_wnut_model

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0581
Precision: 0.9128
Recall: 0.9097
F1: 0.9112
Accuracy: 0.9802

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0802	1.0	3750	0.0687	0.8897	0.8952	0.8924	0.9760
0.0519	2.0	7500	0.0581	0.9128	0.9097	0.9112	0.9802
0.0342	3.0	11250	0.0593	0.9174	0.9172	0.9173	0.9815
0.0253	4.0	15000	0.0634	0.9204	0.9200	0.9202	0.9818

Framework versions

Transformers 4.37.0
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0