results – AI Model by sarehef | AlphaNeural AI

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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results

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: 0.4223
Accuracy: 0.846
F1: 0.8493
Precision: 0.8189
Recall: 0.8821

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: 1e-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	F1	Precision	Recall
No log	1.0	313	0.3867	0.82	0.8352	0.76	0.9268
0.4105	2.0	626	0.3713	0.84	0.8485	0.7943	0.9106
0.4105	3.0	939	0.4171	0.842	0.8364	0.8523	0.8211
0.2565	4.0	1252	0.4223	0.846	0.8493	0.8189	0.8821

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1