xlmroberta_clir_back – AI Model by Shijia | AlphaNeural AI

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Shijia/
xlmroberta_clir_back

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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xlmroberta_clir_back

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: 0.0152
Spearman Corr: 0.8972

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: 32
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Spearman Corr
No log	1.0	206	0.0300	0.6949
0.041	2.0	413	0.0230	0.7671
0.041	3.0	619	0.0183	0.8169
0.0219	4.0	826	0.0154	0.8516
0.0219	5.0	1032	0.0146	0.8698
0.0133	6.0	1239	0.0150	0.8869
0.0133	7.0	1445	0.0152	0.8972

Framework versions

Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0