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vp-xlmr-base-dsc – AI Model by MiuN2k3 | AlphaNeural AI

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MiuN2k3/
vp-xlmr-base-dsc

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0

text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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vp-xlmr-base-dsc

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

eval_loss: 0.4589
eval_accuracy: 0.8317
eval_f1: 0.8313
eval_precision: 0.8337
eval_recall: 0.8317
eval_runtime: 105.9688
eval_samples_per_second: 51.468
eval_steps_per_second: 6.436
epoch: 1.8868
step: 3000

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1