bart-abs-1509-0313-lr-0.0003-bs-8-maxep-6

roequitz/bart-abs-1509-0313-lr-0.0003-bs-8-maxep-6

bart-abs-1509-0313-lr-0.0003-bs-8-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: 9b1b7ff1

Base models

sshleifer/distilbart-xsum-12-6

Model card

From the Hugging Face model README

bart-abs-1509-0313-lr-0.0003-bs-8-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: 7.2543
Rouge/rouge1: 0.3097
Rouge/rouge2: 0.0856
Rouge/rougel: 0.2463
Rouge/rougelsum: 0.2464
Bertscore/bertscore-precision: 0.8589
Bertscore/bertscore-recall: 0.8656
Bertscore/bertscore-f1: 0.8622
Meteor: 0.2246
Gen Len: 36.0

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: 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: 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
1.3455	1.0	109	4.8900	0.3002	0.06	0.2217	0.2214	0.8741	0.8561	0.8649	0.2198	32.0
0.7475	2.0	218	5.6171	0.2599	0.0592	0.202	0.2017	0.8553	0.8626	0.8589	0.2583	43.0
0.5078	3.0	327	6.1951	0.2722	0.0714	0.2029	0.2031	0.8612	0.8618	0.8615	0.2582	44.0
0.3719	4.0	436	6.6790	0.3035	0.072	0.2428	0.2429	0.8724	0.8571	0.8646	0.2108	29.0
0.3026	5.0	545	7.0205	0.3101	0.0691	0.2302	0.2302	0.8569	0.8665	0.8616	0.2291	43.0
0.2546	6.0	654	7.2543	0.3097	0.0856	0.2463	0.2464	0.8589	0.8656	0.8622	0.2246	36.0

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