roberta-finetuned-solvencia-v1 – AI Model by mnavas | AlphaNeural AI

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mnavas/
roberta-finetuned-solvencia-v1

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta-finetuned-solvencia-v1

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

Loss: 0.4141
Accuracy: 0.8919
F1: 0.8919
Precision: 0.8919
Recall: 0.8919

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: 8
eval_batch_size: 8
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	Precision	Recall
No log	1.0	333	0.3781	0.8544	0.8544	0.8544	0.8544
0.4429	2.0	666	0.3295	0.8679	0.8679	0.8679	0.8679
0.4429	3.0	999	0.3664	0.8784	0.8784	0.8784	0.8784
0.3512	4.0	1332	0.4602	0.8649	0.8649	0.8649	0.8649
0.2975	5.0	1665	0.4721	0.8889	0.8889	0.8889	0.8889
0.2975	6.0	1998	0.4141	0.8919	0.8919	0.8919	0.8919
0.2499	7.0	2331	0.4054	0.8889	0.8889	0.8889	0.8889
0.2132	8.0	2664	0.4878	0.8829	0.8829	0.8829	0.8829
0.2132	9.0	2997	0.4867	0.8904	0.8904	0.8904	0.8904
0.1812	10.0	3330	0.5339	0.8889	0.8889	0.8889	0.8889

Framework versions

Transformers 4.16.2
Pytorch 1.9.1
Datasets 1.18.4
Tokenizers 0.11.6