xlm-roberta-base-vmw-finetuned-RC – AI Model by Kuongan | AlphaNeural AI

You can deploy this model and start earning money today!

Kuongan/
xlm-roberta-base-vmw-finetuned-RC

like

0

text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

Views

No views yet

xlm-roberta-base-vmw-finetuned-RC

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: 0.2861
F1: 0.0
Roc Auc: 0.5
Accuracy: 0.4758

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: 32
eval_batch_size: 32
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.4136	1.0	78	0.2861	0.0	0.5	0.4758
0.2945	2.0	156	0.2878	0.0	0.5	0.4758
0.2909	3.0	234	0.2844	0.0	0.5	0.4758
0.2978	4.0	312	0.2854	0.0	0.5	0.4758
0.2881	5.0	390	0.2837	0.0	0.5	0.4758

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0