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

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patpizio/
xlmr-et-en-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-et-en-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: 0.5476
R Squared: 0.2710
Mae: 0.5508
Pearson R: 0.6399

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	0.4918	0.3453	0.5703	0.5987
0.7759	2.0	876	0.4742	0.3687	0.5147	0.6788
0.5858	3.0	1314	0.4901	0.3476	0.5239	0.6641
0.4156	4.0	1752	0.4853	0.3539	0.5293	0.6553
0.3151	5.0	2190	0.5476	0.2710	0.5508	0.6399

Framework versions

Transformers 4.34.1
Pytorch 2.0.1+cu117
Datasets 2.14.6
Tokenizers 0.14.1