bart-abs-1509-0313-lr-0.0003-bs-2-maxep-6

roequitz/bart-abs-1509-0313-lr-0.0003-bs-2-maxep-6

bart-abs-1509-0313-lr-0.0003-bs-2-maxep-6 is a machine learning model from roequitz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

License: apache-2.0
Model type: bart
Access: Public
Created: Sep 15, 2024
Updated: Sep 15, 2024
SHA: b0bec6c3

Base models

sshleifer/distilbart-xsum-12-6

Model card

From the Hugging Face model README

bart-abs-1509-0313-lr-0.0003-bs-2-maxep-6

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-6 on the None dataset. It achieves the following results on the evaluation set:

Loss: 6.8567
Rouge/rouge1: 0.3035
Rouge/rouge2: 0.072
Rouge/rougel: 0.2428
Rouge/rougelsum: 0.2429
Bertscore/bertscore-precision: 0.8724
Bertscore/bertscore-recall: 0.8571
Bertscore/bertscore-f1: 0.8646
Meteor: 0.2108
Gen Len: 29.0

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: 0.0003
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge/rouge1	Rouge/rouge2	Rouge/rougel	Rouge/rougelsum	Bertscore/bertscore-precision	Bertscore/bertscore-recall	Bertscore/bertscore-f1	Meteor	Gen Len
2.4741	1.0	434	4.0269	0.2771	0.0691	0.2057	0.2053	0.8702	0.8596	0.8648	0.233	39.0
3.0848	2.0	868	3.9978	0.2554	0.0651	0.2183	0.2183	0.8646	0.8589	0.8617	0.2022	29.1364
1.9491	3.0	1302	4.4524	0.2722	0.0714	0.2029	0.2031	0.8612	0.8618	0.8615	0.2582	47.0
1.0603	4.0	1736	5.4022	0.2465	0.0593	0.2071	0.2071	0.8464	0.858	0.8521	0.2294	42.0
0.5921	5.0	2170	6.1146	0.3035	0.072	0.2428	0.2429	0.8724	0.8571	0.8646	0.2108	29.0
0.3762	6.0	2604	6.8567	0.3035	0.072	0.2428	0.2429	0.8724	0.8571	0.8646	0.2108	29.0

Framework versions

Transformers 4.44.0
Pytorch 2.4.0
Datasets 2.21.0
Tokenizers 0.19.1

Type: bart
License: apache-2.0
Created: Sep 15, 2024
Updated: Sep 15, 2024