distilbert_base_data_wnut_17 – AI Model by Pongprecha | AlphaNeural AI

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Pongprecha/
distilbert_base_data_wnut_17

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token-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert_base_data_wnut_17

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

Loss: 0.2833
Precision: 0.5246
Recall: 0.3855
F1: 0.4444
Accuracy: 0.9461

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	213	0.2740	0.6152	0.2919	0.3960	0.9404
No log	2.0	426	0.2568	0.5997	0.3679	0.4561	0.9450
0.1764	3.0	639	0.2844	0.6269	0.3457	0.4456	0.9464
0.1764	4.0	852	0.2963	0.5564	0.3522	0.4313	0.9459
0.0526	5.0	1065	0.2833	0.5246	0.3855	0.4444	0.9461

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1