plbart-finetuned-unitTest-1000

This model is a fine-tuned version of uclanlp/plbart-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0000
• Bleu: 0.0000

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: 2e-05
• train_batch_size: 10
• eval_batch_size: 10
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu
No log	1.0	92	0.9023	0.0000
No log	2.0	184	0.8401	0.0000
No log	3.0	276	0.8096	0.0000
No log	4.0	368	0.7942	0.0000
No log	5.0	460	0.7848	0.0000
0.943	6.0	552	0.7818	0.0000
0.943	7.0	644	0.7911	0.0000
0.943	8.0	736	0.7874	0.0000
0.943	9.0	828	0.7970	0.0000
0.943	10.0	920	0.8062	0.0000
0.5025	11.0	1012	0.8085	0.0000
0.5025	12.0	1104	0.8179	0.0000
0.5025	13.0	1196	0.8360	0.0000
0.5025	14.0	1288	0.8385	0.0000
0.5025	15.0	1380	0.8470	0.0000
0.5025	16.0	1472	0.8556	0.0000
0.3309	17.0	1564	0.8619	0.0000
0.3309	18.0	1656	0.8701	0.0000
0.3309	19.0	1748	0.8827	0.0000
0.3309	20.0	1840	0.8871	0.0000
0.3309	21.0	1932	0.8970	0.0000
0.2266	22.0	2024	0.8984	0.0000
0.2266	23.0	2116	0.9051	0.0000
0.2266	24.0	2208	0.9188	0.0000
0.2266	25.0	2300	0.9205	0.0000
0.2266	26.0	2392	0.9278	0.0000
0.2266	27.0	2484	0.9333	0.0000
0.1639	28.0	2576	0.9456	0.0000
0.1639	29.0	2668	0.9454	0.0000
0.1639	30.0	2760	0.9522	0.0000
0.1639	31.0	2852	0.9513	0.0000
0.1639	32.0	2944	0.9554	0.0000
0.1251	33.0	3036	0.9661	0.0000
0.1251	34.0	3128	0.9698	0.0000
0.1251	35.0	3220	0.9750	0.0000
0.1251	36.0	3312	0.9722	0.0000
0.1251	37.0	3404	0.9780	0.0000
0.1251	38.0	3496	0.9789	0.0000
0.1019	39.0	3588	0.9825	0.0000
0.1019	40.0	3680	0.9913	0.0000
0.1019	41.0	3772	0.9906	0.0000
0.1019	42.0	3864	0.9922	0.0000
0.1019	43.0	3956	0.9937	0.0000
0.0863	44.0	4048	0.9981	0.0000
0.0863	45.0	4140	0.9979	0.0000
0.0863	46.0	4232	0.9984	0.0000
0.0863	47.0	4324	0.9970	0.0000
0.0863	48.0	4416	1.0003	0.0000
0.0783	49.0	4508	0.9993	0.0000
0.0783	50.0	4600	1.0000	0.0000

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.13.1
• Tokenizers 0.13.3