paper_feedback_intent

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

• Loss: 0.3621
• Accuracy: 0.9302
• Precision: 0.9307
• Recall: 0.9302
• F1: 0.9297

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.9174	1.0	11	0.7054	0.7907	0.7903	0.7907	0.7861
0.6917	2.0	22	0.4665	0.8140	0.8134	0.8140	0.8118
0.4276	3.0	33	0.3326	0.9070	0.9065	0.9070	0.9041
0.2656	4.0	44	0.3286	0.9070	0.9065	0.9070	0.9041
0.1611	5.0	55	0.3044	0.9302	0.9307	0.9302	0.9297
0.1025	6.0	66	0.3227	0.9302	0.9307	0.9302	0.9297
0.0799	7.0	77	0.3216	0.9302	0.9307	0.9302	0.9297
0.0761	8.0	88	0.3529	0.9302	0.9307	0.9302	0.9297
0.0479	9.0	99	0.3605	0.9302	0.9307	0.9302	0.9297
0.0358	10.0	110	0.3621	0.9302	0.9307	0.9302	0.9297

Framework versions

• Transformers 4.17.0
• Pytorch 1.10.0+cu111
• Datasets 2.0.0
• Tokenizers 0.11.6