finetuned-distilbert-hatexplainV2 – AI Model by uboza10300 | AlphaNeural AI

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uboza10300/
finetuned-distilbert-hatexplainV2

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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finetuned-distilbert-hatexplainV2

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

Loss: 1.1306
Accuracy: 0.6845
Precision: 0.6876
Recall: 0.6845
F1: 0.6849

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.723	1.0	962	0.7320	0.6826	0.6766	0.6826	0.6703
0.6337	2.0	1924	0.7344	0.6857	0.6847	0.6857	0.6852
0.3821	3.0	2886	0.9051	0.6722	0.6885	0.6722	0.6759
0.1811	4.0	3848	1.1789	0.6743	0.6787	0.6743	0.6759

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu118
Datasets 3.1.0
Tokenizers 0.21.0