xlm-roberta-base-finetuned-punctuation-2 – AI Model by hylmar | AlphaNeural AI

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hylmar/
xlm-roberta-base-finetuned-punctuation-2

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token-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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xlm-roberta-base-finetuned-punctuation-2

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: 0.0312
F1: 0.0

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: 5e-05
train_batch_size: 24
eval_batch_size: 24
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: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.0263	1.0	834	0.0409	0.0
0.014	2.0	1668	0.0291	0.0
0.0087	3.0	2502	0.0312	0.0

Framework versions

Transformers 4.48.0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0