README.md

metadata

license: apache-2.0
base_model: Buseak/spellcorrector_20_02_050_qwerty_v11
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: spellcorrector_20_02_050_qwerty_v13
    results: []

spellcorrector_20_02_050_qwerty_v13

This model is a fine-tuned version of Buseak/spellcorrector_20_02_050_qwerty_v11 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0000
• Precision: 1.0
• Recall: 0.9995
• F1: 0.9997
• Accuracy: 1.0000

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: 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
0.0398	1.0	967	0.0161	0.9941	0.9898	0.9919	0.9953
0.0227	2.0	1934	0.0103	0.9952	0.9919	0.9935	0.9970
0.017	3.0	2901	0.0072	0.9936	0.9957	0.9946	0.9978
0.0126	4.0	3868	0.0048	0.9978	0.9946	0.9962	0.9986
0.0104	5.0	4835	0.0034	0.9989	0.9973	0.9981	0.9990
0.0082	6.0	5802	0.0022	0.9989	0.9979	0.9984	0.9993
0.0064	7.0	6769	0.0015	0.9989	0.9973	0.9981	0.9996
0.0055	8.0	7736	0.0013	0.9995	0.9989	0.9992	0.9996
0.0042	9.0	8703	0.0007	0.9989	0.9979	0.9984	0.9998
0.0035	10.0	9670	0.0004	0.9995	0.9989	0.9992	0.9999
0.0032	11.0	10637	0.0003	0.9995	0.9989	0.9992	0.9999
0.0025	12.0	11604	0.0002	0.9995	0.9989	0.9992	1.0000
0.0022	13.0	12571	0.0002	0.9995	0.9989	0.9992	1.0000
0.002	14.0	13538	0.0001	1.0	0.9989	0.9995	1.0000
0.0015	15.0	14505	0.0001	0.9995	1.0	0.9997	1.0000
0.0013	16.0	15472	0.0001	0.9995	1.0	0.9997	1.0000
0.0012	17.0	16439	0.0001	1.0	1.0	1.0	1.0000
0.001	18.0	17406	0.0000	1.0	0.9995	0.9997	1.0000
0.0009	19.0	18373	0.0000	1.0	0.9995	0.9997	1.0000
0.0009	20.0	19340	0.0000	1.0	0.9995	0.9997	1.0000

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.1
• Tokenizers 0.15.2