results_english – AI Model by AvianaKahn | AlphaNeural AI

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AvianaKahn/
results_english

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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results_english

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: 1.5695
Accuracy: 0.7230
Precision: 0.7226
Recall: 0.7230
F1: 0.7227

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	Precision	Recall	F1
No log	1.0	264	0.8641	0.6679	0.6875	0.6679	0.6553
0.8815	2.0	528	0.7834	0.7116	0.7226	0.7116	0.7142
0.8815	3.0	792	0.8200	0.7211	0.7216	0.7211	0.7188
0.6553	4.0	1056	0.8568	0.7211	0.7214	0.7211	0.7212
0.6553	5.0	1320	0.8613	0.7211	0.7215	0.7211	0.7212
0.4667	6.0	1584	1.0583	0.7230	0.7225	0.7230	0.7210
0.4667	7.0	1848	1.3072	0.7438	0.7449	0.7438	0.7420
0.3729	8.0	2112	1.5295	0.7192	0.7189	0.7192	0.7189
0.3729	9.0	2376	1.5407	0.7192	0.7176	0.7192	0.7181
0.2622	10.0	2640	1.5695	0.7230	0.7226	0.7230	0.7227

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.19.1