Training Loss	Epoch	Step	Validation Loss
5.9891	0.24	500	5.0538
4.7513	0.48	1000	4.6760
4.4523	0.72	1500	4.4485
4.2602	0.96	2000	4.3053
4.0617	1.21	2500	4.2166
3.9742	1.45	3000	4.1365
3.9095	1.69	3500	4.0632
3.8462	1.93	4000	3.9949
3.6761	2.17	4500	3.9718
3.6346	2.41	5000	3.9336
3.613	2.65	5500	3.8883
3.5949	2.89	6000	3.8502
3.4561	3.13	6500	3.8626
3.387	3.38	7000	3.8393
3.3931	3.62	7500	3.8152
3.395	3.86	8000	3.7882
3.2751	4.1	8500	3.8162
3.1697	4.34	9000	3.8117
3.1949	4.58	9500	3.7952
3.1957	4.82	10000	3.7726
3.1301	5.06	10500	3.8013
2.9449	5.3	11000	3.8132
2.9803	5.54	11500	3.8048
2.9921	5.79	12000	3.7903
2.9654	6.03	12500	3.8054
2.7336	6.27	13000	3.8363
2.7653	6.51	13500	3.8379
2.7754	6.75	14000	3.8285
2.777	6.99	14500	3.8186
2.5506	7.23	15000	3.8731
2.5598	7.47	15500	3.8769
2.5731	7.71	16000	3.8768
2.5762	7.96	16500	3.8744
2.4267	8.2	17000	3.9055
2.4121	8.44	17500	3.9110
2.4249	8.68	18000	3.9133
2.4157	8.92	18500	3.9140
2.366	9.16	19000	3.9237
2.3398	9.4	19500	3.9252
2.3398	9.64	20000	3.9263
2.3365	9.88	20500	3.9262

NasimB/gpt2-2-og-concat-modified-aochild

gpt2-2-og-concat-modified-aochild