Bainbridge/dialogpt-medium-no_ear - AI Model Zoo

dialogpt-medium-no_ear

This model is a fine-tuned version of microsoft/DialoGPT-medium on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5659

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 21
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss
9.109	0.01	10	9.8250
8.6669	0.02	20	8.9632
5.0713	0.03	30	4.2372
1.5919	0.04	40	1.2643
0.957	0.05	50	1.0243
1.0602	0.06	60	0.9280
0.9131	0.07	70	0.8479
0.8981	0.08	80	0.7994
0.6697	0.09	90	0.7674
0.9282	0.1	100	0.7433
0.9447	0.11	110	0.7271
0.7462	0.12	120	0.7156
0.7161	0.13	130	0.7040
0.8005	0.14	140	0.6934
0.579	0.15	150	0.6848
0.8563	0.16	160	0.6770
0.6635	0.17	170	0.6692
0.8981	0.18	180	0.6613
0.731	0.19	190	0.6552
0.9141	0.2	200	0.6492
0.5798	0.21	210	0.6446
0.6765	0.22	220	0.6400
0.621	0.23	230	0.6356
0.601	0.24	240	0.6330
0.5373	0.25	250	0.6301
0.64	0.26	260	0.6261
0.6474	0.27	270	0.6224
0.6433	0.28	280	0.6197
0.604	0.29	290	0.6167
0.6947	0.3	300	0.6143
0.606	0.31	310	0.6116
0.6329	0.32	320	0.6103
0.5827	0.33	330	0.6086
0.5401	0.34	340	0.6074
0.6682	0.35	350	0.6066
0.6235	0.36	360	0.6039
0.6753	0.37	370	0.6018
0.6582	0.38	380	0.6001
0.5886	0.39	390	0.5995
0.6826	0.4	400	0.5983
0.5701	0.41	410	0.5973
0.7211	0.42	420	0.5962
0.6857	0.43	430	0.5944
0.6894	0.44	440	0.5922
0.6034	0.45	450	0.5920
0.6199	0.46	460	0.5925
0.6487	0.47	470	0.5904
0.5674	0.48	480	0.5884
0.4604	0.49	490	0.5876
0.5617	0.5	500	0.5865
0.5553	0.51	510	0.5852
0.6245	0.52	520	0.5846
0.5015	0.53	530	0.5837
0.6115	0.54	540	0.5836
0.5197	0.55	550	0.5831
0.6451	0.56	560	0.5820
0.6348	0.57	570	0.5817
0.5413	0.58	580	0.5803
0.6283	0.59	590	0.5795
0.5502	0.6	600	0.5789
0.6853	0.61	610	0.5776
0.5457	0.62	620	0.5770
0.6369	0.63	630	0.5762
0.7152	0.64	640	0.5756
0.534	0.65	650	0.5759
0.5276	0.66	660	0.5753
0.6566	0.67	670	0.5750
0.504	0.68	680	0.5746
0.5552	0.69	690	0.5740
0.4891	0.7	700	0.5746
0.6463	0.71	710	0.5743
0.5943	0.72	720	0.5732
0.5833	0.73	730	0.5726
0.5904	0.74	740	0.5719
0.5971	0.75	750	0.5718
0.5906	0.76	760	0.5710
0.6268	0.77	770	0.5701
0.5872	0.78	780	0.5698
0.571	0.79	790	0.5690
0.6224	0.8	800	0.5686
0.5397	0.81	810	0.5683
0.5658	0.82	820	0.5683
0.4248	0.83	830	0.5680
0.5334	0.84	840	0.5674
0.5338	0.85	850	0.5672
0.641	0.86	860	0.5669
0.5601	0.87	870	0.5660
0.6031	0.88	880	0.5654
0.5738	0.89	890	0.5652
0.5619	0.9	900	0.5655
0.4863	0.91	910	0.5667
0.5421	0.92	920	0.5659

Framework versions

Transformers 4.27.4
Pytorch 1.11.0+cu113
Datasets 2.11.0
Tokenizers 0.12.1