bart-abs-1509-0313-lr-3e-06-bs-8-maxep-10

roequitz/bart-abs-1509-0313-lr-3e-06-bs-8-maxep-10

bart-abs-1509-0313-lr-3e-06-bs-8-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: 88fa859c

Base models

sshleifer/distilbart-xsum-12-6

Model card

From the Hugging Face model README

bart-abs-1509-0313-lr-3e-06-bs-8-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: 6.7933
Rouge/rouge1: 0.2524
Rouge/rouge2: 0.0705
Rouge/rougel: 0.2098
Rouge/rougelsum: 0.2104
Bertscore/bertscore-precision: 0.8386
Bertscore/bertscore-recall: 0.8631
Bertscore/bertscore-f1: 0.8506
Meteor: 0.2495
Gen Len: 47.8636

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: 8
eval_batch_size: 8
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
0.2585	1.0	109	6.7188	0.323	0.081	0.2516	0.2521	0.8764	0.8641	0.8702	0.2583	36.0
0.3824	2.0	218	6.7602	0.2515	0.0697	0.2094	0.21	0.8374	0.8631	0.85	0.2474	48.0
0.3739	3.0	327	6.7409	0.3111	0.0793	0.2212	0.2213	0.8659	0.864	0.8649	0.228	36.0
0.3565	4.0	436	6.7314	0.2439	0.0504	0.2065	0.2067	0.8544	0.8581	0.8562	0.229	45.0
0.3514	5.0	545	6.7648	0.2553	0.0701	0.2111	0.2116	0.839	0.8634	0.8509	0.2466	47.4545
0.3434	6.0	654	6.7689	0.271	0.0725	0.2029	0.2034	0.8612	0.8618	0.8614	0.2584	45.0
0.335	7.0	763	6.7845	0.2722	0.0714	0.2029	0.2031	0.8612	0.8618	0.8615	0.2582	45.0
0.337	8.0	872	6.7870	0.2601	0.0623	0.1995	0.1999	0.8579	0.8595	0.8586	0.2431	45.0
0.3328	9.0	981	6.7950	0.2515	0.0697	0.2094	0.21	0.8374	0.8631	0.85	0.2474	48.0
0.34	10.0	1090	6.7933	0.2524	0.0705	0.2098	0.2104	0.8386	0.8631	0.8506	0.2495	47.8636

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