mt5-small-finetuned-summarization

ahmedshark/mt5-small-finetuned-summarization

mt5-small-finetuned-summarization is a summarization model from ahmedshark. Use it when you need a shorter version of a longer text. 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

Task: Summarization
Library: transformers
License: apache-2.0
Model type: mt5
Access: Public
Created: Nov 2, 2024
Updated: Nov 4, 2024
SHA: c397794f

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Base models

google/mt5-small

Model card

From the Hugging Face model README

mt5-small-finetuned-summarization

This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.5678

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: 0.0005
train_batch_size: 8
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 90
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
3.0615	0.128	100	3.1638
3.461	0.256	200	2.8180
3.2633	0.384	300	2.7739
3.2169	0.512	400	2.6986
3.1099	0.64	500	2.6516
3.1311	0.768	600	2.6042
3.0676	0.896	700	2.5785

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0

Task: Summarization
Library: transformers
Type: mt5
License: apache-2.0
Created: Nov 2, 2024
Updated: Nov 4, 2024