roberta-base-finetuned-paperconc3 – AI Model by reyhanemyr | AlphaNeural AI

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reyhanemyr/
roberta-base-finetuned-paperconc3

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta-base-finetuned-paperconc3

This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1262
Precision: 0.7736
Recall: 0.7442
F1: 0.7586
Accuracy: 0.9673

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	81	0.2172	0.6049	0.5180	0.5581	0.9433
No log	2.0	162	0.1489	0.7606	0.6448	0.6979	0.9582
No log	3.0	243	0.1262	0.7736	0.7442	0.7586	0.9673
No log	4.0	324	0.1288	0.7614	0.7759	0.7686	0.9666
No log	5.0	405	0.1340	0.7226	0.8372	0.7757	0.9633
No log	6.0	486	0.1356	0.7151	0.8436	0.7740	0.9625
0.1495	7.0	567	0.1365	0.7414	0.8245	0.7808	0.9688
0.1495	8.0	648	0.1555	0.7261	0.8351	0.7768	0.9635
0.1495	9.0	729	0.1597	0.7548	0.8393	0.7948	0.9669
0.1495	10.0	810	0.1605	0.7467	0.8351	0.7884	0.9666

Framework versions

Transformers 4.27.2
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2