test-results-concat – AI Model by tlttl | AlphaNeural AI

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test-results-concat

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text-classification

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test-results-concat

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

Loss: 0.9408
Accuracy: 0.6012

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: 8
eval_batch_size: 8
seed: 123
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0408	0.33	5000	0.9773	0.5697
0.9442	0.67	10000	0.9701	0.5853
0.9579	1.0	15000	0.9502	0.5895
0.8867	1.33	20000	0.9467	0.5897
0.8819	1.67	25000	0.9371	0.5893
0.8748	2.0	30000	0.9408	0.6012
0.7759	2.33	35000	0.9734	0.5968
0.7599	2.67	40000	0.9722	0.5948
0.7626	3.0	45000	0.9654	0.5975

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.1