furina_arq_corr_0.0001

This model is a fine-tuned version of yihongLiu/furina on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0472
• Spearman Corr: nan

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: 0.0001
• 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	0.92	200	0.0471	-0.0481
No log	1.84	400	0.0471	0.0145
0.0512	2.76	600	0.0487	nan
0.0512	3.69	800	0.0477	nan
0.0506	4.61	1000	0.0482	0.0156
0.0506	5.53	1200	0.0475	nan
0.0503	6.45	1400	0.0473	nan
0.0503	7.37	1600	0.0490	nan
0.0502	8.29	1800	0.0483	nan
0.0502	9.22	2000	0.0482	nan
0.05	10.14	2200	0.0471	nan
0.05	11.06	2400	0.0477	nan
0.0503	11.98	2600	0.0472	nan

Framework versions

• Transformers 4.37.2
• Pytorch 2.2.0+cu121
• Datasets 2.17.0
• Tokenizers 0.15.2