distilbert-base-uncased_3epoch10 – AI Model by dianamihalache27 | AlphaNeural AI

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dianamihalache27/
distilbert-base-uncased_3epoch10

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text-classification

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distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased_3epoch10

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: 2.5208
Accuracy: 0.6988
F1: 0.3192
Precision: 0.4537
Recall: 0.2462
Precision Sarcastic: 0.4537
Recall Sarcastic: 0.2462
F1 Sarcastic: 0.3192

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Precision Sarcastic	Recall Sarcastic	F1 Sarcastic
No log	1.0	174	2.6411	0.7017	0.1481	0.4091	0.0905	0.4091	0.0905	0.1481
No log	2.0	348	2.0172	0.7104	0.3045	0.4889	0.2211	0.4889	0.2211	0.3045
0.0495	3.0	522	1.9688	0.6844	0.4097	0.4419	0.3819	0.4419	0.3819	0.4097
0.0495	4.0	696	2.1007	0.7075	0.2671	0.4744	0.1859	0.4744	0.1859	0.2671
0.0495	5.0	870	2.4142	0.7104	0.2744	0.4872	0.1910	0.4872	0.1910	0.2744
0.032	6.0	1044	2.3684	0.6931	0.4132	0.4573	0.3769	0.4573	0.3769	0.4132
0.032	7.0	1218	2.5365	0.7118	0.2754	0.4935	0.1910	0.4935	0.1910	0.2754
0.032	8.0	1392	2.5712	0.7046	0.2756	0.4643	0.1960	0.4643	0.1960	0.2756
0.0112	9.0	1566	2.4974	0.6960	0.3127	0.4444	0.2412	0.4444	0.2412	0.3127
0.0112	10.0	1740	2.5208	0.6988	0.3192	0.4537	0.2462	0.4537	0.2462	0.3192

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1