xlm-roberta-base_arb_loss_2e-05 – AI Model by Shijia | AlphaNeural AI

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Shijia/
xlm-roberta-base_arb_loss_2e-05

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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xlm-roberta-base_arb_loss_2e-05

This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0231
Spearman Corr: 0.7741

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: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Spearman Corr
No log	0.85	200	0.0223	0.7795
No log	1.69	400	0.0234	0.7737
0.0017	2.54	600	0.0228	0.7753
0.0017	3.38	800	0.0232	0.7759
0.0014	4.23	1000	0.0233	0.7716
0.0014	5.07	1200	0.0242	0.7750
0.0014	5.92	1400	0.0249	0.7719
0.0013	6.77	1600	0.0221	0.7774
0.0013	7.61	1800	0.0231	0.7774
0.0011	8.46	2000	0.0226	0.7767
0.0011	9.3	2200	0.0241	0.7753
0.0011	10.15	2400	0.0229	0.7721
0.0011	10.99	2600	0.0240	0.7732
0.0011	11.84	2800	0.0239	0.7758
0.001	12.68	3000	0.0235	0.7710
0.001	13.53	3200	0.0231	0.7741

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cu121
Datasets 2.17.0
Tokenizers 0.15.2