xlm-roberta-base-mar-finetuned-augmentation-LUNAR – AI Model by sercetexam9 | AlphaNeural AI

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sercetexam9/
xlm-roberta-base-mar-finetuned-augmentation-LUNAR

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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xlm-roberta-base-mar-finetuned-augmentation-LUNAR

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

Loss: 0.1378
F1: 0.8898
Roc Auc: 0.9346
Accuracy: 0.8238

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.3996	1.0	202	0.3715	0.1141	0.5475	0.2841
0.2292	2.0	404	0.2025	0.7924	0.8493	0.7208
0.1613	3.0	606	0.1802	0.8019	0.8587	0.7705
0.1317	4.0	808	0.1499	0.8479	0.8922	0.7965
0.1036	5.0	1010	0.1472	0.8555	0.8978	0.8002
0.0984	6.0	1212	0.1364	0.8655	0.9107	0.8127
0.0791	7.0	1414	0.1304	0.8739	0.9194	0.8176
0.0501	8.0	1616	0.1371	0.8749	0.9207	0.8102
0.0602	9.0	1818	0.1436	0.8726	0.9193	0.8176
0.0375	10.0	2020	0.1407	0.8790	0.9223	0.8139
0.0437	11.0	2222	0.1422	0.8815	0.9302	0.8189
0.0297	12.0	2424	0.1444	0.8842	0.9270	0.8251
0.0196	13.0	2626	0.1378	0.8898	0.9346	0.8238
0.0193	14.0	2828	0.1463	0.8825	0.9276	0.8176
0.0238	15.0	3030	0.1481	0.8834	0.9277	0.8238
0.0167	16.0	3232	0.1464	0.8884	0.9328	0.8251
0.0113	17.0	3434	0.1469	0.8834	0.9272	0.8238

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0