xlmroberta_clir_eng_back – AI Model by Shijia | AlphaNeural AI

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Shijia/
xlmroberta_clir_eng_back

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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xlmroberta_clir_eng_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: 0.0125
Spearman Corr: 0.9059

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	0.0267	0.7148
0.0432	2.0	413	0.0217	0.7759
0.0432	3.0	619	0.0182	0.8263
0.0214	4.0	826	0.0154	0.8606
0.0214	5.0	1032	0.0147	0.8792
0.0138	6.0	1239	0.0134	0.8876
0.0138	7.0	1445	0.0152	0.8925
0.01	8.0	1652	0.0114	0.9026
0.01	9.0	1858	0.0117	0.9039
0.0083	9.98	2060	0.0125	0.9059

Framework versions

Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0