bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch

This model is a fine-tuned version of Ameer05/model-token-repo on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.5216
• Rouge1: 59.5791
• Rouge2: 51.3273
• Rougel: 56.9984
• Rougelsum: 59.1424

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: 5.6e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
No log	0.91	5	2.0124	53.776	46.7427	50.7565	53.5502
No log	1.91	10	1.6353	61.8019	53.8614	58.9744	61.339
No log	2.91	15	1.5321	59.7045	51.5968	57.0823	59.2417
No log	3.91	20	1.4569	62.4379	54.5464	59.9202	61.9242
1.5608	4.91	25	1.4613	63.3808	55.8818	61.432	63.0208
1.5608	5.91	30	1.4321	59.6761	50.9812	56.7977	59.1214
1.5608	6.91	35	1.4753	62.6439	54.7158	60.3831	62.1046
1.5608	7.91	40	1.4783	60.2735	52.7462	57.77	59.9725
0.6428	8.91	45	1.4974	62.8691	54.9062	60.3496	62.5132
0.6428	9.91	50	1.5216	59.5791	51.3273	56.9984	59.1424

Framework versions

• Transformers 4.15.0
• Pytorch 1.9.1
• Datasets 1.18.4
• Tokenizers 0.10.3