distilroberta-topic-classification – AI Model by valurank | AlphaNeural AI

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valurank/
distilroberta-topic-classification

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text-classification

generated_from_trainer

valurank/Topic_Classification

autotrain_compatible

endpoints_compatible

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distilroberta-topic-classification

This model is a fine-tuned version of distilroberta-topic-base on a dataset of headlines. It achieves the following results on the evaluation set:

Loss: 2.235735
F1: 0.756

Training and evaluation data

The following data sources were used:

22k News articles classified into 120 different topics from Hugging face

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 12345
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 16
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1
2.3851	1.0	561	2.3445	0.6495
2.1441	2.0	1122	2.1980	0.7019
1.9992	3.0	1683	2.1720	0.7189
1.8384	4.0	2244	2.1425	0.7403
1.7468	5.0	2805	2.1666	0.7453
1.6360	6.0	3366	2.1779	0.7456
1.5935	7.0	3927	2.2003	0.7555
1.5460	8.0	4488	2.2157	0.7575
1.5510	9.0	5049	2.2300	0.7536
1.5097	10.0	5610	2.2357	0.7547

Framework versions

Transformers 4.35.2
Pytorch 2.1.0
Datasets 2.15.0
Tokenizers 0.15.0