INHA_in_short

JulietteBenguigui142/INHA_in_short

INHA_in_short is a machine learning model from JulietteBenguigui142. 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. --

Downloads · 30 days

28% of all-time downloads

All-time downloads

Public

Parameters

60.5M

1.7 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors242 MB · 99%

At a glance

Library: transformers
License: apache-2.0
Model type: t5
Access: Public
Created: May 10, 2024
Updated: May 10, 2024
SHA: 44fed14e

Base models

google-t5/t5-small

Model card

From the Hugging Face model README

INHA_in_short

This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4008
Rouge1: 0.532
Rouge2: 0.4546
Rougel: 0.5242
Rougelsum: 0.524
Gen Len: 18.9616

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.9095	1.0	866	0.4647	0.5128	0.4329	0.5049	0.5049	18.9624
0.5092	2.0	1732	0.4192	0.5287	0.4509	0.521	0.5207	18.9622
0.4636	3.0	2598	0.4035	0.5332	0.4557	0.5253	0.5252	18.9616
0.461	4.0	3464	0.4008	0.532	0.4546	0.5242	0.524	18.9616

Framework versions

Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Library: transformers
Type: t5
License: apache-2.0
Created: May 10, 2024
Updated: May 10, 2024