Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.99	60	2.7933	0.3216	0.0997	0.1522	0.2833
No log	1.99	120	0.3818	0.9075	0.8989	0.9032	0.9224
No log	2.99	180	0.1156	0.9602	0.9607	0.9605	0.9721
No log	3.99	240	0.0911	0.9634	0.9650	0.9642	0.9748
No log	4.99	300	0.0794	0.9664	0.9679	0.9671	0.9772
No log	5.99	360	0.0741	0.9670	0.9697	0.9683	0.9781
No log	6.99	420	0.0695	0.9683	0.9702	0.9693	0.9787
No log	7.99	480	0.0688	0.9686	0.9700	0.9693	0.9789
0.7281	8.99	540	0.0675	0.9688	0.9703	0.9695	0.9789
0.7281	9.99	600	0.0670	0.9687	0.9705	0.9696	0.9791
0.7281	10.99	660	0.0658	0.9696	0.9702	0.9699	0.9792
0.7281	11.99	720	0.0670	0.9684	0.9715	0.9700	0.9793
0.7281	12.99	780	0.0672	0.9689	0.9711	0.9700	0.9792
0.7281	13.99	840	0.0678	0.9698	0.9708	0.9703	0.9796
0.7281	14.99	900	0.0681	0.9696	0.9714	0.9705	0.9796
0.7281	15.99	960	0.0706	0.9696	0.9711	0.9703	0.9795
0.0484	16.99	1020	0.0725	0.9694	0.9705	0.9699	0.9793
0.0484	17.99	1080	0.0735	0.9689	0.9705	0.9697	0.9791
0.0484	18.99	1140	0.0745	0.9690	0.9705	0.9698	0.9792
0.0484	19.99	1200	0.0769	0.9690	0.9706	0.9698	0.9791
0.0484	20.99	1260	0.0797	0.9691	0.9703	0.9697	0.9791
0.0484	21.99	1320	0.0808	0.9689	0.9705	0.9697	0.9791
0.0484	22.99	1380	0.0838	0.9691	0.9702	0.9697	0.9791
0.0484	23.99	1440	0.0861	0.9685	0.9704	0.9695	0.9789
0.0289	24.99	1500	0.0879	0.9684	0.9698	0.9691	0.9787
0.0289	25.99	1560	0.0887	0.9684	0.9703	0.9694	0.9789
0.0289	26.99	1620	0.0910	0.9684	0.9698	0.9691	0.9787
0.0289	27.99	1680	0.0924	0.9684	0.9697	0.9691	0.9787
0.0289	28.99	1740	0.0950	0.9693	0.9692	0.9693	0.9788
0.0289	29.99	1800	0.0962	0.9692	0.9697	0.9694	0.9789
0.0289	30.99	1860	0.0977	0.9687	0.9699	0.9693	0.9787
0.0289	31.99	1920	0.0979	0.9688	0.9699	0.9694	0.9788
0.0289	32.99	1980	0.1000	0.9687	0.9698	0.9692	0.9788
0.018	33.99	2040	0.1021	0.9688	0.9698	0.9693	0.9788
0.018	34.99	2100	0.1037	0.9687	0.9701	0.9694	0.9788
0.018	35.99	2160	0.1035	0.9688	0.9703	0.9696	0.9790
0.018	36.99	2220	0.1042	0.9688	0.9700	0.9694	0.9789
0.018	37.99	2280	0.1053	0.9685	0.9699	0.9692	0.9787
0.018	38.99	2340	0.1052	0.9689	0.9700	0.9695	0.9789
0.018	39.99	2400	0.1054	0.9688	0.9700	0.9694	0.9788

Framework versions

Transformers 4.25.1
Pytorch 1.12.0
Datasets 2.18.0
Tokenizers 0.13.2

pranaydeeps/lettuce_pos_en_mono

pos_final_mono_en

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

pranaydeeps/
lettuce_pos_en_mono