Training Loss	Epoch	Step	Validation Loss	Gen Len
No log	1.0	8	6.6371	19.0
6.8242	2.0	16	5.2780	19.0
6.8242	3.0	24	4.4851	19.0
5.345	4.0	32	3.7656	19.0
5.345	5.0	40	3.0462	19.0
4.0321	6.0	48	2.4729	19.0
3.2425	7.0	56	2.1585	11.7931
3.2425	8.0	64	2.0606	0.0
2.8344	9.0	72	2.0090	0.0
2.8344	10.0	80	1.9443	0.0
2.6721	11.0	88	1.8702	0.0
2.6721	12.0	96	1.8071	0.0
2.5019	13.0	104	1.7541	0.0
2.3339	14.0	112	1.7014	0.0
2.3339	15.0	120	1.6502	0.0
2.2227	16.0	128	1.6094	0.0
2.2227	17.0	136	1.5746	0.0
2.1738	18.0	144	1.5353	0.0
2.1738	19.0	152	1.5066	0.0
2.054	20.0	160	1.4870	0.0
1.9707	21.0	168	1.4581	0.0
1.9707	22.0	176	1.4359	0.0
1.96	23.0	184	1.4032	0.0
1.96	24.0	192	1.3737	0.0
1.7402	25.0	200	1.3482	0.0
1.7402	26.0	208	1.3257	0.0
1.7044	27.0	216	1.3047	0.0
1.751	28.0	224	1.2861	0.0
1.751	29.0	232	1.2644	0.0
1.6414	30.0	240	1.2353	0.0
1.6414	31.0	248	1.2160	0.0
1.6418	32.0	256	1.1991	0.0
1.6418	33.0	264	1.1937	0.0
1.6258	34.0	272	1.1762	0.0
1.6102	35.0	280	1.1632	0.0
1.6102	36.0	288	1.1498	0.0
1.5266	37.0	296	1.1361	0.0
1.5266	38.0	304	1.1205	10.4828
1.5756	39.0	312	1.1108	10.4828
1.5756	40.0	320	1.1028	10.4828
1.5136	41.0	328	1.0937	10.4828
1.529	42.0	336	1.0837	10.4828
1.529	43.0	344	1.0714	11.7931
1.4738	44.0	352	1.0599	13.1034
1.4738	45.0	360	1.0514	13.1034
1.4521	46.0	368	1.0467	13.1034
1.4521	47.0	376	1.0438	13.1034
1.4758	48.0	384	1.0358	13.1034
1.4698	49.0	392	1.0264	13.1034
1.4698	50.0	400	1.0205	17.6897
1.3355	51.0	408	1.0159	18.3448
1.3355	52.0	416	1.0087	19.0
1.36	53.0	424	1.0040	19.0
1.36	54.0	432	1.0005	19.0
1.3025	55.0	440	0.9955	19.0
1.2773	56.0	448	0.9910	19.0
1.2773	57.0	456	0.9873	19.0
1.3006	58.0	464	0.9840	19.0
1.3006	59.0	472	0.9826	19.0
1.3037	60.0	480	0.9813	19.0
1.3037	61.0	488	0.9765	19.0
1.3133	62.0	496	0.9717	19.0
1.2601	63.0	504	0.9671	19.0
1.2601	64.0	512	0.9637	19.0
1.2442	65.0	520	0.9610	19.0
1.2442	66.0	528	0.9585	19.0
1.2394	67.0	536	0.9568	19.0
1.2394	68.0	544	0.9546	19.0
1.2746	69.0	552	0.9509	19.0
1.233	70.0	560	0.9478	19.0
1.233	71.0	568	0.9452	19.0
1.2382	72.0	576	0.9424	19.0
1.2382	73.0	584	0.9400	19.0
1.2603	74.0	592	0.9379	19.0
1.2603	75.0	600	0.9357	19.0
1.2028	76.0	608	0.9338	19.0
1.2755	77.0	616	0.9330	19.0
1.2755	78.0	624	0.9316	19.0
1.244	79.0	632	0.9303	19.0
1.244	80.0	640	0.9291	19.0
1.115	81.0	648	0.9281	19.0
1.115	82.0	656	0.9272	19.0
1.2373	83.0	664	0.9258	19.0
1.2035	84.0	672	0.9243	19.0
1.2035	85.0	680	0.9231	19.0
1.1881	86.0	688	0.9216	19.0
1.1881	87.0	696	0.9205	19.0
1.1713	88.0	704	0.9200	19.0
1.1713	89.0	712	0.9191	19.0
1.1984	90.0	720	0.9184	19.0
1.2879	91.0	728	0.9177	19.0
1.2879	92.0	736	0.9174	19.0
1.1823	93.0	744	0.9171	19.0
1.1823	94.0	752	0.9170	19.0
1.2293	95.0	760	0.9166	19.0
1.2293	96.0	768	0.9162	19.0
1.2154	97.0	776	0.9160	19.0
1.1625	98.0	784	0.9158	19.0
1.1625	99.0	792	0.9156	19.0
1.1679	100.0	800	0.9156	19.0

Framework versions

Transformers 4.33.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

manahil1/Code_Corrector_Model

Code_Corrector_Model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

manahil1/
Code_Corrector_Model