distilbert-base-fact-updates – AI Model by rishavranaut | AlphaNeural AI

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rishavranaut/
distilbert-base-fact-updates

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert-base-fact-updates

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.8173

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 600
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss
0.6606	1.0	222	0.6163
0.5134	2.0	444	0.5272
0.5031	3.0	666	0.5244
0.4677	4.0	888	0.4792
0.3751	5.0	1110	0.4875
0.3456	6.0	1332	0.5194
0.3616	7.0	1554	0.5328
0.256	8.0	1776	0.5634
0.2339	9.0	1998	0.5952
0.1846	10.0	2220	0.6313
0.0828	11.0	2442	0.7221
0.1649	12.0	2664	0.7298
0.1107	13.0	2886	0.7864
0.1027	14.0	3108	0.8157
0.0887	15.0	3330	0.8173

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1