fine-tuned-NLI-multilingual-with-xlm-roberta-large – AI Model by muhammadravi251001 | AlphaNeural AI

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muhammadravi251001/
fine-tuned-NLI-multilingual-with-xlm-roberta-large

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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fine-tuned-NLI-multilingual-with-xlm-roberta-large

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

Loss: 0.4158
Accuracy: 0.8600
F1: 0.8612

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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 128
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	Accuracy	F1	Validation Loss
0.4647	0.5	1613	0.8396	0.8403	0.4262
0.4437	1.0	3226	0.8511	0.8522	0.4042
0.3956	1.5	4839	0.3783	0.8604	0.8602
0.3639	2.0	6452	0.3913	0.8592	0.8600
0.323	2.5	8065	0.3783	0.8657	0.8659
0.3186	3.0	9678	0.3850	0.8626	0.8625
0.2485	3.5	11291	0.4326	0.8597	0.8592
0.2509	4.0	12904	0.4158	0.8600	0.8612

Framework versions

Transformers 4.26.1
Pytorch 2.0.1+cu117
Datasets 2.2.0
Tokenizers 0.13.3