xlm_r_base-finetuned_after_mrp-v2-winter-morning-8 – AI Model by haturusinghe | AlphaNeural AI

You can deploy this model and start earning money today!

haturusinghe/
xlm_r_base-finetuned_after_mrp-v2-winter-morning-8

like

0

text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

Views

No views yet

xlm_r_base-finetuned_after_mrp-v2-winter-morning-8

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: 0.3928
Precision 0: 0.8692
Precision 1: 0.8174
Recall 0: 0.8768
Recall 1: 0.8069
F1 0: 0.8729
F1 1: 0.8121
Precision Weighted: 0.8481
Recall Weighted: 0.8484
F1 Weighted: 0.8482
F1 Macro: 0.8425

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: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision 0	Precision 1	Recall 0	Recall 1	F1 0	F1 1	Precision Weighted	Recall Weighted	F1 Weighted	F1 Macro
0.5435	1.0	469	0.4939	0.7696	0.9088	0.9603	0.5793	0.8544	0.7076	0.8261	0.8056	0.7948	0.7810
0.383	2.0	938	0.3987	0.8647	0.7743	0.8391	0.8079	0.8517	0.7907	0.8280	0.8264	0.8269	0.8212
0.376	3.0	1407	0.3737	0.8511	0.8220	0.8855	0.7734	0.8680	0.7970	0.8393	0.84	0.8391	0.8325
0.2841	4.0	1876	0.3928	0.8692	0.8174	0.8768	0.8069	0.8729	0.8121	0.8481	0.8484	0.8482	0.8425
0.225	5.0	2345	0.4836	0.8597	0.8026	0.8667	0.7931	0.8632	0.7978	0.8365	0.8368	0.8366	0.8305

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1