amazon_helpfulness_classification_seqbn_tapt_full_train_add_adapter

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

• Loss: 0.3051
• Accuracy: 0.8778
• F1 Macro: 0.7038

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro
0.3274	1.0	7204	0.3143	0.866	0.6036
0.328	2.0	14408	0.3203	0.8668	0.5893
0.3155	3.0	21612	0.3076	0.8738	0.6825
0.3098	4.0	28816	0.3079	0.8758	0.6805
0.2634	5.0	36020	0.3143	0.873	0.6983
0.2546	6.0	43224	0.3108	0.8756	0.6911
0.2574	7.0	50428	0.3103	0.8718	0.6945
0.2298	8.0	57632	0.3207	0.875	0.6973

Framework versions

• Transformers 4.36.2
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.15.2