xlm-roberta-base-finetuned-marc-en – AI Model by oaaeaaua | AlphaNeural AI

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oaaeaaua/
xlm-roberta-base-finetuned-marc-en

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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xlm-roberta-base-finetuned-marc-en

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: 0.6572
Accuracy: 0.7805
Recall: 0.6445
Precision: 0.5522
F1: 0.5948

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	Precision	F1
0.5098	1.0	309	0.4999	0.7498	0.0	0.0	0.0
0.4698	2.0	618	0.4456	0.7959	0.3456	0.6816	0.4586
0.3921	3.0	927	0.4620	0.8094	0.4561	0.6765	0.5448
0.3771	4.0	1236	0.4446	0.8172	0.5156	0.6766	0.5852
0.3454	5.0	1545	0.4567	0.8249	0.5609	0.6828	0.6159
0.2713	6.0	1854	0.4726	0.8136	0.6176	0.6301	0.6237
0.272	7.0	2163	0.5024	0.8108	0.6317	0.6194	0.6255
0.2478	8.0	2472	0.5689	0.8051	0.6516	0.6021	0.6259
0.1869	9.0	2781	0.6018	0.8044	0.7082	0.5910	0.6443
0.1575	10.0	3090	0.6700	0.8108	0.4986	0.6617	0.5687
0.1411	11.0	3399	0.7287	0.8157	0.5581	0.6545	0.6024
0.1014	12.0	3708	0.8177	0.8086	0.5269	0.6436	0.5794

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1