train – AI Model by julesyego | AlphaNeural AI

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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train

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

Loss: 0.1100
F1: 0.6074
Roc Auc: 0.7538
Accuracy: 0.8966

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: 5e-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	F1	Roc Auc	Accuracy
0.2023	1.0	5261	0.1159	0.5889	0.7525	0.8851
0.1663	2.0	10522	0.1100	0.6074	0.7538	0.8966
0.1472	3.0	15783	0.1132	0.5736	0.7679	0.8634
0.1312	4.0	21044	0.1159	0.5975	0.7462	0.8911
0.1175	5.0	26305	0.1289	0.5922	0.7390	0.8936
0.1036	6.0	31566	0.1380	0.6062	0.7463	0.897
0.089	7.0	36827	0.1440	0.5927	0.7395	0.894
0.077	8.0	42088	0.1579	0.5998	0.7463	0.8944
0.0661	9.0	47349	0.1662	0.5933	0.7382	0.8956
0.0584	10.0	52610	0.1665	0.5940	0.7424	0.8922

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Tokenizers 0.13.2