bart-abs-1509-0313-lr-3e-06-bs-2-maxep-10

roequitz/bart-abs-1509-0313-lr-3e-06-bs-2-maxep-10

bart-abs-1509-0313-lr-3e-06-bs-2-maxep-10 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: a9e47b5a

Base models

sshleifer/distilbart-xsum-12-6

Model card

From the Hugging Face model README

bart-abs-1509-0313-lr-3e-06-bs-2-maxep-10

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: 6.8719
Rouge/rouge1: 0.2515
Rouge/rouge2: 0.0697
Rouge/rougel: 0.2094
Rouge/rougelsum: 0.21
Bertscore/bertscore-precision: 0.8374
Bertscore/bertscore-recall: 0.8631
Bertscore/bertscore-f1: 0.85
Meteor: 0.2474
Gen Len: 48.0

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: 3e-06
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: 10
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
0.3072	1.0	434	6.4601	0.2705	0.0674	0.225	0.2255	0.861	0.855	0.8579	0.2231	30.4545
0.3542	2.0	868	6.6824	0.3111	0.0793	0.2212	0.2213	0.8659	0.864	0.8649	0.228	36.0
0.3893	3.0	1302	6.6462	0.3097	0.0856	0.2463	0.2464	0.8585	0.8656	0.862	0.2246	36.0
0.363	4.0	1736	6.7283	0.3097	0.0856	0.2463	0.2464	0.8585	0.8656	0.862	0.2246	36.0
0.3521	5.0	2170	6.7742	0.3097	0.0856	0.2463	0.2464	0.8585	0.8656	0.862	0.2246	36.0
0.3425	6.0	2604	6.8107	0.2439	0.0504	0.2065	0.2067	0.8544	0.8581	0.8562	0.229	45.0
0.3306	7.0	3038	6.8433	0.2522	0.07	0.2096	0.2101	0.8377	0.8632	0.8502	0.2476	47.9364
0.3259	8.0	3472	6.8653	0.2515	0.0697	0.2094	0.21	0.8374	0.8631	0.85	0.2474	48.0
0.3228	9.0	3906	6.8621	0.2515	0.0697	0.2094	0.21	0.8374	0.8631	0.85	0.2474	48.0
0.3193	10.0	4340	6.8719	0.2515	0.0697	0.2094	0.21	0.8374	0.8631	0.85	0.2474	48.0

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