bart_large_cnn_samsum_model_10epoch

This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	200	1.4282	0.0066	0.4109	0.2008	0.3084	0.3085	59.755
No log	2.0	400	1.5080	0.0066	0.4214	0.2027	0.3175	0.3175	59.3862
1.2171	3.0	600	1.5348	0.0066	0.4093	0.1949	0.3071	0.307	60.2062
1.2171	4.0	800	1.7114	0.0066	0.4092	0.1928	0.3067	0.3066	60.38
0.6518	5.0	1000	1.8757	0.0066	0.4149	0.1935	0.3118	0.3117	59.5
0.6518	6.0	1200	2.0521	0.0066	0.4126	0.1902	0.3107	0.3108	60.335
0.6518	7.0	1400	2.1551	0.0066	0.4138	0.1917	0.3117	0.3115	60.1888
0.3371	8.0	1600	2.4051	0.0066	0.4132	0.1913	0.3116	0.3116	60.28
0.3371	9.0	1800	2.4850	0.0066	0.4146	0.1897	0.3129	0.3131	60.7375
0.2072	10.0	2000	2.5260	0.0066	0.4165	0.1911	0.3142	0.3143	60.615