my_distilbert_model – AI Model by PrasadAvidi | AlphaNeural AI

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PrasadAvidi/
my_distilbert_model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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my_distilbert_model

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: 0.2117
Accuracy: 0.9225
F1: 0.8756
Precision: 0.8748
Recall: 0.8766

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	Accuracy	F1	Precision	Recall
0.2521	1.0	1000	0.2238	0.925	0.8895	0.8727	0.9188
0.1495	2.0	2000	0.1740	0.9315	0.8901	0.9069	0.8793
0.1137	3.0	3000	0.1736	0.9275	0.8856	0.8837	0.8894
0.0862	4.0	4000	0.2029	0.926	0.8843	0.8758	0.8950
0.0562	5.0	5000	0.2117	0.9225	0.8756	0.8748	0.8766

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1