Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	1	0.6220	0.7188
No log	2.0	2	0.6220	0.7188
No log	3.0	3	0.6219	0.7188
No log	4.0	4	0.6218	0.7188
No log	5.0	5	0.6217	0.7188
No log	6.0	6	0.6216	0.7188
No log	7.0	7	0.6215	0.7188
No log	8.0	8	0.6214	0.7188
No log	9.0	9	0.6213	0.7188
0.6205	10.0	10	0.6211	0.7188
0.6205	11.0	11	0.6210	0.7188
0.6205	12.0	12	0.6208	0.7188
0.6205	13.0	13	0.6206	0.7188
0.6205	14.0	14	0.6204	0.7188
0.6205	15.0	15	0.6202	0.7188
0.6205	16.0	16	0.6200	0.7188
0.6205	17.0	17	0.6198	0.7188
0.6205	18.0	18	0.6196	0.7188
0.6205	19.0	19	0.6194	0.7188
0.6217	20.0	20	0.6192	0.6875
0.6217	21.0	21	0.6190	0.6875
0.6217	22.0	22	0.6189	0.6875
0.6217	23.0	23	0.6187	0.6875
0.6217	24.0	24	0.6186	0.6875
0.6217	25.0	25	0.6185	0.6875
0.6217	26.0	26	0.6184	0.6875
0.6217	27.0	27	0.6182	0.6875
0.6217	28.0	28	0.6181	0.6875
0.6217	29.0	29	0.6180	0.6875
0.6001	30.0	30	0.6179	0.6875
0.6001	31.0	31	0.6178	0.6875
0.6001	32.0	32	0.6178	0.6875
0.6001	33.0	33	0.6177	0.6875
0.6001	34.0	34	0.6177	0.6875
0.6001	35.0	35	0.6177	0.6875
0.6001	36.0	36	0.6177	0.6875
0.6001	37.0	37	0.6178	0.6875
0.6001	38.0	38	0.6178	0.6875
0.6001	39.0	39	0.6179	0.6562
0.5564	40.0	40	0.6180	0.6562
0.5564	41.0	41	0.6181	0.6562
0.5564	42.0	42	0.6181	0.6562
0.5564	43.0	43	0.6180	0.6562
0.5564	44.0	44	0.6179	0.6562
0.5564	45.0	45	0.6177	0.6562
0.5564	46.0	46	0.6174	0.6562
0.5564	47.0	47	0.6171	0.6562
0.5564	48.0	48	0.6171	0.6562
0.5564	49.0	49	0.6170	0.6562
0.5364	50.0	50	0.6172	0.6562
0.5364	51.0	51	0.6172	0.625
0.5364	52.0	52	0.6172	0.625
0.5364	53.0	53	0.6170	0.625
0.5364	54.0	54	0.6165	0.625
0.5364	55.0	55	0.6161	0.625
0.5364	56.0	56	0.6155	0.625
0.5364	57.0	57	0.6149	0.625
0.5364	58.0	58	0.6142	0.625
0.5364	59.0	59	0.6137	0.625
0.489	60.0	60	0.6132	0.625
0.489	61.0	61	0.6126	0.625
0.489	62.0	62	0.6121	0.625
0.489	63.0	63	0.6116	0.625
0.489	64.0	64	0.6111	0.5938
0.489	65.0	65	0.6107	0.5938
0.489	66.0	66	0.6103	0.625
0.489	67.0	67	0.6098	0.625
0.489	68.0	68	0.6093	0.625
0.489	69.0	69	0.6088	0.625
0.4517	70.0	70	0.6086	0.625
0.4517	71.0	71	0.6080	0.625
0.4517	72.0	72	0.6068	0.625
0.4517	73.0	73	0.6052	0.625
0.4517	74.0	74	0.6035	0.625
0.4517	75.0	75	0.6014	0.625
0.4517	76.0	76	0.5993	0.625
0.4517	77.0	77	0.5974	0.625
0.4517	78.0	78	0.5951	0.6562
0.4517	79.0	79	0.5932	0.6875
0.4066	80.0	80	0.5912	0.6875
0.4066	81.0	81	0.5895	0.6875
0.4066	82.0	82	0.5880	0.6875
0.4066	83.0	83	0.5868	0.6875
0.4066	84.0	84	0.5856	0.7188
0.4066	85.0	85	0.5843	0.7188
0.4066	86.0	86	0.5829	0.7188
0.4066	87.0	87	0.5816	0.7188
0.4066	88.0	88	0.5803	0.7188
0.4066	89.0	89	0.5790	0.7188
0.3548	90.0	90	0.5778	0.7188
0.3548	91.0	91	0.5766	0.75
0.3548	92.0	92	0.5754	0.75
0.3548	93.0	93	0.5743	0.75
0.3548	94.0	94	0.5732	0.75
0.3548	95.0	95	0.5719	0.75
0.3548	96.0	96	0.5706	0.75
0.3548	97.0	97	0.5693	0.75
0.3548	98.0	98	0.5680	0.75
0.3548	99.0	99	0.5669	0.75
0.3182	100.0	100	0.5659	0.75
0.3182	101.0	101	0.5648	0.7812
0.3182	102.0	102	0.5636	0.7812
0.3182	103.0	103	0.5624	0.7812
0.3182	104.0	104	0.5612	0.7812
0.3182	105.0	105	0.5599	0.7812
0.3182	106.0	106	0.5584	0.7812
0.3182	107.0	107	0.5567	0.8125
0.3182	108.0	108	0.5548	0.8125
0.3182	109.0	109	0.5530	0.8125
0.2758	110.0	110	0.5513	0.8125
0.2758	111.0	111	0.5498	0.8125
0.2758	112.0	112	0.5483	0.8125
0.2758	113.0	113	0.5468	0.7812
0.2758	114.0	114	0.5452	0.7812
0.2758	115.0	115	0.5438	0.7812
0.2758	116.0	116	0.5429	0.7812
0.2758	117.0	117	0.5420	0.75
0.2758	118.0	118	0.5411	0.75
0.2758	119.0	119	0.5400	0.7188
0.2399	120.0	120	0.5390	0.7188
0.2399	121.0	121	0.5375	0.7188
0.2399	122.0	122	0.5356	0.75
0.2399	123.0	123	0.5340	0.75
0.2399	124.0	124	0.5322	0.75
0.2399	125.0	125	0.5303	0.7812
0.2399	126.0	126	0.5281	0.75
0.2399	127.0	127	0.5259	0.7812
0.2399	128.0	128	0.5240	0.7812
0.2399	129.0	129	0.5215	0.7812
0.2062	130.0	130	0.5191	0.75
0.2062	131.0	131	0.5167	0.75
0.2062	132.0	132	0.5143	0.75
0.2062	133.0	133	0.5121	0.75
0.2062	134.0	134	0.5102	0.75
0.2062	135.0	135	0.5085	0.7812
0.2062	136.0	136	0.5071	0.7812
0.2062	137.0	137	0.5059	0.7812
0.2062	138.0	138	0.5048	0.7812
0.2062	139.0	139	0.5035	0.7812
0.1688	140.0	140	0.5023	0.7812
0.1688	141.0	141	0.5011	0.7812
0.1688	142.0	142	0.5001	0.7812
0.1688	143.0	143	0.4991	0.7812
0.1688	144.0	144	0.4980	0.7812
0.1688	145.0	145	0.4970	0.7812
0.1688	146.0	146	0.4960	0.7812
0.1688	147.0	147	0.4950	0.7812
0.1688	148.0	148	0.4938	0.7812
0.1688	149.0	149	0.4926	0.7812
0.1364	150.0	150	0.4916	0.7812

Framework versions

Transformers 4.32.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.4.0
Tokenizers 0.13.3

simonycl/best_model-sst-2-16-21

best_model-sst-2-16-21

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

simonycl/
best_model-sst-2-16-21