intent_analysis_3labels_v1 – AI Model by adriansanz | AlphaNeural AI

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adriansanz/
intent_analysis_3labels_v1

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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intent_analysis_V1_TOTAL

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: 0.0167
Accuracy: 0.9969
Precision: 0.9969
Recall: 0.9969
F1: 0.9969

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: 64
eval_batch_size: 64
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	214	0.0432	0.9899	0.9899	0.9899	0.9899
No log	2.0	428	0.0252	0.9952	0.9952	0.9952	0.9952
0.0885	3.0	642	0.0263	0.9956	0.9956	0.9956	0.9956
0.0885	4.0	856	0.0222	0.9962	0.9962	0.9962	0.9962
0.0086	5.0	1070	0.0167	0.9969	0.9969	0.9969	0.9969

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3