canine_sent_2304v1

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

• Loss: 0.0000
• Precision: 1.0
• Recall: 1.0
• F1: 1.0
• Accuracy: 1.0

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: 2
• eval_batch_size: 2
• 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
0.0218	1.0	781	0.0051	0.9531	0.9434	0.9482	0.9980
0.0059	2.0	1562	0.0028	0.9712	0.9714	0.9713	0.9989
0.0043	3.0	2343	0.0018	0.9733	0.9980	0.9855	0.9994
0.0021	4.0	3124	0.0010	0.9873	0.9991	0.9932	0.9997
0.0018	5.0	3905	0.0005	0.9952	0.9984	0.9968	0.9998
0.0012	6.0	4686	0.0002	0.9988	0.9986	0.9987	0.9999
0.0007	7.0	5467	0.0001	0.9989	0.9986	0.9988	1.0000
0.0007	8.0	6248	0.0001	0.9998	0.9991	0.9995	1.0000
0.0004	9.0	7029	0.0000	0.9998	1.0	0.9999	1.0000
0.0004	10.0	7810	0.0000	0.9998	0.9995	0.9996	1.0000
0.0003	11.0	8591	0.0001	0.9996	0.9998	0.9997	1.0000
0.0002	12.0	9372	0.0000	1.0	0.9998	0.9999	1.0000
0.0002	13.0	10153	0.0000	1.0	0.9998	0.9999	1.0000
0.0001	14.0	10934	0.0000	1.0	0.9998	0.9999	1.0000
0.0001	15.0	11715	0.0000	1.0	1.0	1.0	1.0

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3