xlmr_sarc_op_tmp – AI Model by Naren-Kandasamy | AlphaNeural AI

You can deploy this model and start earning money today!

Naren-Kandasamy/
xlmr_sarc_op_tmp

like

0

text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

text-embeddings-inference

endpoints_compatible

Views

No views yet

xlmr_sarc_op_tmp

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: 0.6858
Accuracy: 0.6862
F1: 0.6576

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: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 8
mixed_precision_training: Native AMP
label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	111	0.6549	0.6253	0.3847
No log	2.0	222	0.6271	0.6591	0.6248
No log	3.0	333	0.6140	0.7111	0.6658
No log	4.0	444	0.6418	0.6840	0.6118
0.6265	5.0	555	0.6683	0.6456	0.6337
0.6265	6.0	666	0.6513	0.7043	0.6745
0.6265	7.0	777	0.6755	0.6953	0.6656
0.6265	8.0	888	0.6858	0.6862	0.6576

Framework versions

Transformers 4.57.2
Pytorch 2.9.0+cu126
Datasets 4.5.0
Tokenizers 0.22.2