Training Loss	Epoch	Step	Validation Loss
5.9917	0.24	500	5.0580
4.751	0.48	1000	4.6761
4.4491	0.72	1500	4.4474
4.2552	0.96	2000	4.3018
4.0564	1.21	2500	4.2130
3.9694	1.45	3000	4.1354
3.9064	1.69	3500	4.0597
3.8419	1.93	4000	3.9915
3.6722	2.17	4500	3.9682
3.6318	2.41	5000	3.9315
3.6106	2.65	5500	3.8886
3.5928	2.89	6000	3.8514
3.4548	3.13	6500	3.8612
3.3861	3.38	7000	3.8411
3.393	3.62	7500	3.8154
3.3954	3.86	8000	3.7894
3.2757	4.1	8500	3.8165
3.1711	4.34	9000	3.8133
3.196	4.58	9500	3.7968
3.1968	4.82	10000	3.7750
3.1316	5.06	10500	3.8042
2.9476	5.3	11000	3.8150
2.9825	5.54	11500	3.8057
2.9945	5.79	12000	3.7922
2.9682	6.03	12500	3.8095
2.7376	6.27	13000	3.8392
2.7689	6.51	13500	3.8374
2.78	6.75	14000	3.8313
2.7801	6.99	14500	3.8215
2.5564	7.23	15000	3.8731
2.5648	7.47	15500	3.8790
2.5779	7.71	16000	3.8779
2.5815	7.96	16500	3.8749
2.4329	8.2	17000	3.9075
2.4187	8.44	17500	3.9123
2.4313	8.68	18000	3.9145
2.4232	8.92	18500	3.9151
2.3723	9.16	19000	3.9246
2.3473	9.4	19500	3.9267
2.3464	9.64	20000	3.9275
2.3445	9.88	20500	3.9275

NasimB/gpt2-3-og-concat-modified-aochild

gpt2-3-og-concat-modified-aochild