distilbert-base-uncased-assignment1 – AI Model by GabrielG228 | AlphaNeural AI

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distilbert-base-uncased-assignment1

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-assignment1

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: 0.1872
Accuracy: 0.935
F1: 0.9349

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: 64
eval_batch_size: 64
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
0.7708	1.0	250	0.2413	0.921	0.9213
0.1928	2.0	500	0.1672	0.9325	0.9319
0.1297	3.0	750	0.1486	0.936	0.9369
0.0983	4.0	1000	0.1368	0.9405	0.9407
0.0825	5.0	1250	0.1488	0.94	0.9400
0.0671	6.0	1500	0.1589	0.937	0.9375
0.0575	7.0	1750	0.1750	0.931	0.9305
0.0466	8.0	2000	0.1781	0.9345	0.9344
0.038	9.0	2250	0.1862	0.934	0.9339
0.0345	10.0	2500	0.1872	0.935	0.9349

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.0.2
Tokenizers 0.19.1