t-5-base-extractive-375

jgibb/t-5-base-extractive-375

t-5-base-extractive-375 is a machine learning model from jgibb. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. 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

Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: Mar 30, 2024
Updated: Mar 31, 2024
SHA: e7822188

Base models

Model card

From the Hugging Face model README

t-5-base-extractive-375

This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.1670
Rouge1: 0.6791
Rouge2: 0.4138
Rougel: 0.6184
Rougelsum: 0.6183
Wer: 0.4846
Bleurt: 0.3314

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: 2e-05
train_batch_size: 6
eval_batch_size: 6
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Wer	Bleurt
No log	0.14	250	1.3197	0.6547	0.3806	0.5905	0.5904	0.5188	0.3009
1.7026	0.27	500	1.2676	0.6613	0.3907	0.5986	0.5985	0.5074	0.3009
1.7026	0.41	750	1.2385	0.6664	0.3964	0.6043	0.6043	0.5023	0.3009
1.3446	0.55	1000	1.2234	0.6691	0.4011	0.6075	0.6074	0.4972	0.3009
1.3446	0.68	1250	1.2089	0.671	0.4033	0.61	0.6098	0.4944	0.3009
1.309	0.82	1500	1.1983	0.673	0.4066	0.6123	0.6121	0.4914	0.3009
1.309	0.96	1750	1.1900	0.6743	0.4078	0.6137	0.6135	0.4897	0.3009
1.2783	1.09	2000	1.1840	0.6744	0.4085	0.614	0.614	0.4889	0.2798
1.2783	1.23	2250	1.1808	0.6758	0.4104	0.6155	0.6154	0.4875	0.2944
1.2683	1.36	2500	1.1763	0.6771	0.4112	0.6165	0.6163	0.4863	0.3153
1.2683	1.5	2750	1.1720	0.6772	0.4117	0.617	0.6168	0.4859	0.4109
1.2469	1.64	3000	1.1701	0.6783	0.4129	0.6178	0.6176	0.485	0.3314
1.2469	1.77	3250	1.1680	0.6786	0.4133	0.6179	0.6177	0.4849	0.3314
1.2171	1.91	3500	1.1670	0.6791	0.4138	0.6184	0.6183	0.4846	0.3314

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Library: transformers
Type: t5
License: apache-2.0
Created: Mar 30, 2024
Updated: Mar 31, 2024