metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: roberta-base-finetuned-papernew5
    results: []

roberta-base-finetuned-papernew5

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

Loss: 0.0864
Precision: 0.7835
Recall: 0.8144
F1: 0.7986
Accuracy: 0.9742

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: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	81	0.1872	0.6657	0.5174	0.5822	0.9511
No log	2.0	162	0.1321	0.6189	0.7912	0.6945	0.9585
No log	3.0	243	0.0864	0.7835	0.8144	0.7986	0.9742
No log	4.0	324	0.0891	0.7532	0.8144	0.7826	0.9723
No log	5.0	405	0.1004	0.7542	0.8399	0.7947	0.9723
No log	6.0	486	0.1197	0.7267	0.8515	0.7842	0.9677
0.1476	7.0	567	0.1237	0.7605	0.8399	0.7982	0.9709
0.1476	8.0	648	0.1104	0.7383	0.8445	0.7879	0.9728
0.1476	9.0	729	0.1179	0.7863	0.8283	0.8068	0.9742
0.1476	10.0	810	0.1150	0.7811	0.8608	0.8190	0.9752
0.1476	11.0	891	0.1273	0.7602	0.8608	0.8074	0.9728
0.1476	12.0	972	0.1230	0.7711	0.8677	0.8166	0.9751
0.014	13.0	1053	0.1280	0.7815	0.8631	0.8203	0.9753
0.014	14.0	1134	0.1285	0.7755	0.8654	0.8180	0.9753
0.014	15.0	1215	0.1336	0.7639	0.8631	0.8105	0.9740

Framework versions

Transformers 4.27.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2