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Youssef320/
finetuned_1L_BERT_newcode_5epoch-f1score

Name: finetuned_1L_BERT_newcode_5epoch-f1score
Availability: InStock

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finetuned_1L_BERT_newcode_5epoch-f1score

This model is a fine-tuned version of Youssef320/LSTM-finetuned-50label-15epoch on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.0134
Top 1 Macro F1 Score: 0.1420
Top 1 Weighted F1score: 0.1923
Top 3 Macro F1 Score: 0.2960
Top3 3 Weighted F1 Score : 0.3853

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: 0.0002
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 2048
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Top 1 Macro F1 Score	Top 1 Weighted F1score	Top 3 Macro F1 Score	Top3 3 Weighted F1 Score
3.2498	0.14	64	3.0549	0.1275	0.1797	0.2717	0.3636
3.1662	0.27	128	3.0345	0.1311	0.1856	0.2767	0.3674
3.16	0.41	192	3.0158	0.1342	0.1886	0.2792	0.3724
3.1154	0.54	256	3.0034	0.1343	0.1880	0.2844	0.3770
3.1257	0.68	320	2.9848	0.1332	0.1876	0.2820	0.3783
3.1227	0.81	384	2.9721	0.1339	0.1887	0.2844	0.3806
3.1058	0.95	448	2.9737	0.1369	0.1916	0.2871	0.3815
3.0486	1.09	512	3.0066	0.1353	0.1873	0.2888	0.3794
3.0286	1.22	576	3.0036	0.1359	0.1884	0.2874	0.3808
3.0181	1.36	640	2.9924	0.1369	0.1894	0.2888	0.3823
3.0251	1.49	704	2.9899	0.1387	0.1916	0.2878	0.3814
3.0482	1.63	768	2.9787	0.1377	0.1900	0.2903	0.3828
3.0565	1.77	832	2.9746	0.1397	0.1928	0.2912	0.3847
3.0563	1.9	896	2.9710	0.1390	0.1936	0.2887	0.3839
2.9363	2.04	960	3.0022	0.1413	0.1952	0.2902	0.3822
2.951	2.17	1024	3.0072	0.1381	0.1908	0.2902	0.3822
2.9839	2.31	1088	3.0027	0.1413	0.1947	0.2890	0.3811
2.9714	2.45	1152	2.9972	0.1411	0.1945	0.2905	0.3829
2.9959	2.58	1216	2.9788	0.1387	0.1905	0.2906	0.3845
2.9932	2.72	1280	2.9875	0.1412	0.1954	0.2905	0.3840
2.9952	2.85	1344	2.9728	0.1403	0.1933	0.2935	0.3862
3.0112	2.99	1408	2.9707	0.1399	0.1921	0.2958	0.3879
2.9005	3.13	1472	3.0190	0.1398	0.1923	0.2912	0.3825
2.9153	3.26	1536	3.0224	0.1400	0.1935	0.2923	0.3814
2.9284	3.4	1600	3.0087	0.1387	0.1917	0.2895	0.3819
2.922	3.53	1664	3.0130	0.1397	0.1918	0.2927	0.3838
2.947	3.67	1728	3.0023	0.1402	0.1923	0.2916	0.3834
2.9538	3.8	1792	2.9948	0.1414	0.1937	0.2944	0.3845
2.9478	3.94	1856	2.9876	0.1420	0.1952	0.2926	0.3852
2.8445	4.08	1920	3.0409	0.1403	0.1912	0.2961	0.3843
2.8498	4.21	1984	3.0378	0.1412	0.1933	0.2942	0.3813
2.8519	4.35	2048	3.0405	0.1422	0.1942	0.2952	0.3825
2.8715	4.48	2112	3.0341	0.1412	0.1941	0.2922	0.3815
2.892	4.62	2176	3.0262	0.1405	0.1936	0.2912	0.3813
2.8952	4.75	2240	3.0241	0.1428	0.1953	0.2944	0.3840
2.9135	4.89	2304	3.0134	0.1420	0.1923	0.2960	0.3853

Framework versions

Transformers 4.20.1
Pytorch 1.12.1+cu102
Datasets 2.0.0
Tokenizers 0.11.0

Youssef320/finetuned_1L_BERT_newcode_5epoch-f1score

finetuned_1L_BERT_newcode_5epoch-f1score

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Youssef320/
finetuned_1L_BERT_newcode_5epoch-f1score