spellcorrector_11_02_050_1_per_word_v5

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: 0.0399
• Precision: 0.9989
• Recall: 0.9946
• F1: 0.9968
• Accuracy: 0.9880

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
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.3884	1.0	967	0.1563	0.9714	0.9635	0.9674	0.9611
0.1648	2.0	1934	0.1297	0.9784	0.9716	0.9750	0.9669
0.1431	3.0	2901	0.1157	0.9924	0.9753	0.9838	0.9698
0.1286	4.0	3868	0.1042	0.9897	0.9807	0.9852	0.9722
0.1201	5.0	4835	0.0969	0.9903	0.9839	0.9871	0.9737
0.1134	6.0	5802	0.0882	0.9903	0.9861	0.9882	0.9757
0.106	7.0	6769	0.0808	0.9935	0.9855	0.9895	0.9773
0.1002	8.0	7736	0.0763	0.9924	0.9861	0.9892	0.9786
0.0945	9.0	8703	0.0696	0.9957	0.9855	0.9906	0.9799
0.0903	10.0	9670	0.0641	0.9919	0.9893	0.9906	0.9813
0.0866	11.0	10637	0.0597	0.9920	0.9925	0.9922	0.9825
0.0822	12.0	11604	0.0557	0.9962	0.9925	0.9944	0.9835
0.0787	13.0	12571	0.0523	0.9978	0.9914	0.9946	0.9843
0.0751	14.0	13538	0.0500	0.9984	0.9946	0.9965	0.9852
0.0715	15.0	14505	0.0467	0.9968	0.9946	0.9957	0.9861
0.0698	16.0	15472	0.0438	0.9995	0.9952	0.9973	0.9868
0.0674	17.0	16439	0.0426	0.9984	0.9952	0.9968	0.9870
0.0652	18.0	17406	0.0410	0.9989	0.9952	0.9970	0.9875
0.0639	19.0	18373	0.0403	0.9989	0.9946	0.9968	0.9879
0.0628	20.0	19340	0.0399	0.9989	0.9946	0.9968	0.9880

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.0
• Tokenizers 0.15.1