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taiypeo/
bart-large-xsum-rouge-3-loss-differentiable-100-cnt-supervised-sequential

Name: bart-large-xsum-rouge-3-loss-differentiable-100-cnt-supervised-sequential
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bart-large-xsum-rouge-3-loss-differentiable-100-cnt-supervised-sequential

This model is a fine-tuned version of taiypeo/bart-large-xsum-sentence-paraphrased-100-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 OptimizerNames.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
0.9903	0.0162	10	1.9863	0.374	0.1508	0.2964	0.2961
0.9839	0.0323	20	2.0204	0.3758	0.1526	0.2978	0.2975
0.9821	0.0485	30	2.0951	0.373	0.1524	0.297	0.2969
0.972	0.0646	40	2.2146	0.3707	0.1509	0.2958	0.2957
0.966	0.0808	50	2.4021	0.3646	0.1469	0.2912	0.2909
0.9645	0.0970	60	2.7506	0.3514	0.1388	0.2813	0.281
0.931	0.1131	70	3.2479	0.336	0.1263	0.2688	0.2686
0.9079	0.1293	80	3.6992	0.3223	0.1152	0.2582	0.258