learning_rate: 0.0001
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5

Training Loss	Epoch	Step	Validation Loss	Accuracy	Perplexity	Bleu
6.0443	0.2806	500	5.9164	0.1901	371.0844	0.0350
5.0429	0.5612	1000	4.8947	0.2638	133.5839	0.0647
4.3531	0.8418	1500	4.2426	0.3176	69.5891	0.0829
3.9503	1.1223	2000	3.8874	0.3517	48.7842	0.1050
3.7613	1.4029	2500	3.7124	0.3672	40.9504	0.1211
3.6548	1.6835	3000	3.5911	0.3780	36.2753	0.1308
3.5531	1.9641	3500	3.5068	0.3860	33.3428	0.1340
3.4344	2.2447	4000	3.4411	0.3920	31.2224	0.1356
3.3743	2.5253	4500	3.3875	0.3972	29.5917	0.1389
3.3443	2.8058	5000	3.3429	0.4016	28.3017	0.1373
3.225	3.0864	5500	3.3080	0.4055	27.3310	0.1419
3.2185	3.3670	6000	3.2781	0.4090	26.5258	0.1463
3.1972	3.6476	6500	3.2500	0.4121	25.7899	0.1453
3.1719	3.9282	7000	3.2268	0.4144	25.1990	0.1465
3.1052	4.2088	7500	3.2109	0.4162	24.8018	0.1472
3.0672	4.4893	8000	3.1978	0.4179	24.4788	0.1469
3.0773	4.7699	8500	3.1864	0.4195	24.2005	0.1476

BluebrainAI/parallel-mean-bottleneck-gpt2-medium-wikitext

parallel-mean-bottleneck-gpt2-medium-wikitext