Training Loss	Epoch	Step	Validation Loss
28.2167	0.06	1000	9.7030
10.4479	0.12	2000	7.5450
8.0306	0.19	3000	6.1969
6.503	0.25	4000	5.3015
5.5406	0.31	5000	4.6363
4.7299	0.38	6000	4.0431
3.9263	0.44	7000	3.6313
3.4111	0.5	8000	3.4830
3.0517	0.56	9000	3.3294
2.7524	0.62	10000	3.2077
2.5402	0.69	11000	3.1094
2.3228	0.75	12000	3.1099
2.1513	0.81	13000	3.0284
2.0418	0.88	14000	3.0155
1.8875	0.94	15000	3.0241
1.756	1.0	16000	3.0165
1.6489	1.06	17000	2.9849
1.5788	1.12	18000	2.9496
1.5368	1.19	19000	2.9500
1.4467	1.25	20000	3.0133
1.381	1.31	21000	2.9631
1.3451	1.38	22000	3.0159
1.2917	1.44	23000	2.9906
1.2605	1.5	24000	3.0006
1.2003	1.56	25000	2.9797
1.1987	1.62	26000	2.9253
1.1703	1.69	27000	3.0044
1.1474	1.75	28000	2.9216
1.0816	1.81	29000	2.9645
1.0709	1.88	30000	3.0439
1.0476	1.94	31000	3.0844
1.0645	2.0	32000	2.9434
1.0204	2.06	33000	2.9386
0.9901	2.12	34000	3.0452
0.9911	2.19	35000	2.9798
0.9706	2.25	36000	2.9919
0.9461	2.31	37000	3.0279
0.9577	2.38	38000	2.9615
0.9466	2.44	39000	2.9988
0.9486	2.5	40000	2.9133
0.9201	2.56	41000	3.0004
0.896	2.62	42000	2.9626
0.8893	2.69	43000	2.9667
0.9028	2.75	44000	2.9543
0.897	2.81	45000	2.8760
0.8664	2.88	46000	2.9894
0.8719	2.94	47000	2.8456
0.8491	3.0	48000	2.9713
0.8402	3.06	49000	2.9738
0.8484	3.12	50000	2.9361
0.8304	3.19	51000	2.8945
0.8208	3.25	52000	2.9625
0.8074	3.31	53000	3.0054
0.8226	3.38	54000	2.9405
0.8185	3.44	55000	2.9047
0.8352	3.5	56000	2.9016
0.8289	3.56	57000	2.9490
0.7918	3.62	58000	2.9621
0.8212	3.69	59000	2.9341
0.7955	3.75	60000	2.9167
0.7724	3.81	61000	2.9409
0.8169	3.88	62000	2.8925
0.7862	3.94	63000	2.9314
0.803	4.0	64000	2.9271
0.7595	4.06	65000	2.9263
0.7931	4.12	66000	2.9400
0.7759	4.19	67000	2.9501
0.7859	4.25	68000	2.9133
0.805	4.31	69000	2.8785
0.7649	4.38	70000	2.9060
0.7692	4.44	71000	2.8868
0.7692	4.5	72000	2.9045
0.7798	4.56	73000	2.8951
0.7812	4.62	74000	2.9068
0.7533	4.69	75000	2.9129
0.7527	4.75	76000	2.9157
0.7652	4.81	77000	2.9053
0.7633	4.88	78000	2.9190
0.7437	4.94	79000	2.9251
0.7653	5.0	80000	2.9188

Framework versions

Transformers 4.12.5
Pytorch 1.10.0+cu111
Datasets 1.5.0
Tokenizers 0.10.3

mimi/Waynehills-NLP-doogie

Waynehills-NLP-doogie

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mimi/
Waynehills-NLP-doogie