xlmr-en-zh-no_shuffled-orig-test1000 – AI Model by patpizio | AlphaNeural AI

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patpizio/
xlmr-en-zh-no_shuffled-orig-test1000

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text-classification

generated_from_trainer

wmt20_mlqe_task1

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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xlmr-en-zh-no_shuffled-orig-test1000

This model is a fine-tuned version of xlm-roberta-base on the wmt20_mlqe_task1 dataset. It achieves the following results on the evaluation set:

Loss: 0.5862
R Squared: -0.1664
Mae: 0.5991
Pearson R: 0.4148

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
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	R Squared	Mae	Pearson R
No log	1.0	438	0.4458	0.1130	0.5377	0.3977
0.7823	2.0	876	0.4252	0.1539	0.5123	0.4517
0.6317	3.0	1314	0.4948	0.0155	0.5423	0.4304
0.4449	4.0	1752	0.5149	-0.0245	0.5577	0.4247
0.3139	5.0	2190	0.5862	-0.1664	0.5991	0.4148

Framework versions

Transformers 4.34.1
Pytorch 2.0.1+cu117
Datasets 2.14.6
Tokenizers 0.14.1