roberta_finetune_CPS_class_weights

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

• Loss: 1.8949
• Accuracy: 0.7267
• F1-micro: 0.7267
• F1-macro: 0.6325

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1-micro	F1-macro
0.7524	1.0	736	1.0201	0.6812	0.6812	0.5511
0.732	2.0	1472	0.9168	0.7233	0.7233	0.6004
0.5315	3.0	2208	0.9742	0.7260	0.7260	0.5957
0.5015	4.0	2944	1.1334	0.7410	0.7410	0.6853
0.2782	5.0	3680	1.2754	0.7158	0.7158	0.6016
0.3866	6.0	4416	1.4692	0.7294	0.7294	0.6228
0.4302	7.0	5152	1.6980	0.7267	0.7267	0.6390
0.1895	8.0	5888	1.7853	0.7322	0.7322	0.6377
0.1945	9.0	6624	1.8803	0.7254	0.7254	0.6183
0.0963	10.0	7360	1.8949	0.7267	0.7267	0.6325

Framework versions

• Transformers 4.42.4
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1