mt5-small-finetuned-mt5-en

ahmeddbahaa/mt5-small-finetuned-mt5-en

mt5-small-finetuned-mt5-en is a summarization model from ahmeddbahaa. 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. --

Downloads · 30 days

3% of all-time downloads

All-time downloads

587

Public

Repo size

4.8 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin1.2 GB · 98%

At a glance

Task: Summarization
Library: transformers
License: apache-2.0
Model type: mt5
Access: Public
Created: Mar 24, 2022
Updated: Mar 24, 2022
SHA: fe112242

Try a prompt

Datasets

xlsum

Model card

From the Hugging Face model README

mt5-small-finetuned-mt5-en

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

Loss: 2.8345
Rouge1: 23.8952
Rouge2: 5.8792
Rougel: 18.6495
Rougelsum: 18.7057

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 10
total_train_batch_size: 40
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
No log	1.0	224	3.0150	24.4639	5.3016	18.3987	18.4963
No log	2.0	448	2.8738	24.5075	5.842	18.8133	18.9072
No log	3.0	672	2.8345	23.8952	5.8792	18.6495	18.7057

Framework versions

Transformers 4.17.0
Pytorch 1.10.0+cu111
Datasets 2.0.0
Tokenizers 0.11.6

Task: Summarization
Library: transformers
Type: mt5
License: apache-2.0
Created: Mar 24, 2022
Updated: Mar 24, 2022