bart-large-cnn-with-generate-finetune-indosum

This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0686
• Rouge1: 0.8873
• Rouge2: 0.8491
• Rougel: 0.8815
• Rougelsum: 0.8815
• Gen Len: 128.9129

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.2591	1.0	4460	0.2573	0.7218	0.6324	0.6969	0.6967	129.0612
0.1657	2.0	8920	0.1600	0.7613	0.6815	0.7401	0.7401	128.9508
0.0945	3.0	13380	0.1157	0.8001	0.7311	0.7837	0.7835	128.9105
0.0508	4.0	17840	0.0976	0.8277	0.7704	0.8152	0.8152	129.0289
0.0296	5.0	22300	0.0853	0.857	0.8087	0.8473	0.8471	128.9257
0.0176	6.0	26760	0.0793	0.8702	0.8279	0.8632	0.8633	128.9113
0.0112	7.0	31220	0.0605	0.8789	0.8377	0.872	0.8721	128.8637
0.0074	8.0	35680	0.0597	0.88	0.84	0.8731	0.8732	128.9305
0.005	9.0	40140	0.0658	0.8822	0.8433	0.8761	0.8761	128.949
0.0036	10.0	44600	0.0686	0.8873	0.8491	0.8815	0.8815	128.9129

Framework versions

• Transformers 4.32.1
• Pytorch 2.0.0
• Datasets 2.12.0
• Tokenizers 0.13.2