HW1_distilbert-base-uncased – AI Model by KudriashovSS | AlphaNeural AI

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KudriashovSS/
HW1_distilbert-base-uncased

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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hw1_distilbert-base-uncased

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: 0.2028
Precision: 0.8302
Recall: 0.8881
F1: 0.8582
Accuracy: 0.9449

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: 0.0002
train_batch_size: 32
eval_batch_size: 32
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	59	0.2135	0.7672	0.8528	0.8078	0.9317
No log	2.0	118	0.1760	0.8181	0.8916	0.8533	0.9397
No log	3.0	177	0.1759	0.8183	0.8963	0.8555	0.9442
No log	4.0	236	0.1900	0.8336	0.8837	0.8579	0.9448
No log	5.0	295	0.2028	0.8302	0.8881	0.8582	0.9449

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3