This model is a fine-tuned version of google/mt5-small on the amazon_reviews_multi dataset (https://huggingface.co/datasets/amazon_reviews_multi), with a filter applied to reviews about books.

The filter_books function is used to filter examples in the data and returns only those that belong to the "book" or "digital ebook purchase" category.

It achieves the following results on the evaluation set:

Loss: 3.0270
Rouge1: 16.8614
Rouge2: 8.3352
Rougel: 16.5595
Rougelsum: 16.5755

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: 5.6e-05
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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
7.376	1.0	1209	3.3114	13.6834	5.4759	13.2778	13.3315
3.9197	2.0	2418	3.1662	15.4107	7.396	15.0443	15.0493
3.5954	3.0	3627	3.0844	15.4126	7.2537	15.0816	15.1281
3.4243	4.0	4836	3.0384	15.9869	7.7568	15.7054	15.6149
3.3145	5.0	6045	3.0512	17.3119	8.412	16.8461	16.7631
3.2597	6.0	7254	3.0237	16.7165	7.9706	16.4276	16.3935
3.2094	7.0	8463	3.0308	17.4737	8.7048	17.0836	17.0624
3.1886	8.0	9672	3.0270	16.8614	8.3352	16.5595	16.5755

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cpu
Datasets 2.14.5
Tokenizers 0.13.3

Natet/mt5-small-finetuned-amazon-en-es

mt5-small-finetuned-amazon-en-es

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Natet/
mt5-small-finetuned-amazon-en-es