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taiypeo/
bart-base-aeslc-sentence-paraphrased-rouge-3-loss-differentiable-10-cnt-supervised-sequential

Name: bart-base-aeslc-sentence-paraphrased-rouge-3-loss-differentiable-10-cnt-supervised-sequential
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bart-base-aeslc-sentence-paraphrased-rouge-3-loss-differentiable-10-cnt-supervised-sequential

This model is a fine-tuned version of taiypeo/bart-base-aeslc-10-cnt-supervised-basic on an unknown dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use adamw_torch_fused 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: 0.06
num_epochs: 5

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
1.5984	0.0022	2	5.2944	0.1685	0.0821	0.1615	0.1617
1.0136	0.0044	4	5.2952	0.1684	0.0821	0.1614	0.1616
1.1632	0.0067	6	5.2969	0.1695	0.0827	0.1625	0.1627
1.8066	0.0089	8	5.2990	0.1698	0.0837	0.1629	0.163
1.6189	0.0111	10	5.3015	0.1708	0.0841	0.1638	0.1639
1.8405	0.0133	12	5.3041	0.1737	0.0856	0.1665	0.1667
1.1221	0.0155	14	5.3071	0.1744	0.0855	0.1672	0.1674
2.0465	0.0177	16	5.3112	0.1755	0.0855	0.1679	0.1678
1.3252	0.0200	18	5.3155	0.1763	0.0858	0.1687	0.1687
1.8633	0.0222	20	5.3208	0.1773	0.0873	0.1699	0.1699
3.6333	0.0244	22	5.3272	0.1787	0.0876	0.1715	0.1716
1.0555	0.0266	24	5.3353	0.1798	0.0884	0.1723	0.1723
1.3045	0.0288	26	5.3454	0.1805	0.0885	0.1727	0.1729
1.0971	0.0311	28	5.3561	0.1826	0.0891	0.1745	0.1746
1.2611	0.0333	30	5.3670	0.184	0.0904	0.1759	0.1762
1.0693	0.0355	32	5.3795	0.1851	0.0908	0.1767	0.177
1.0263	0.0377	34	5.3955	0.1836	0.089	0.1749	0.1753
0.9785	0.0399	36	5.4159	0.1836	0.0889	0.175	0.175
0.9781	0.0421	38	5.4397	0.1827	0.0884	0.1738	0.1739