Downloads · 30 days
11
4% of all-time downloads
convaise-idp/flan-t5-base-finetuned-length_control_token
flan-t5-base-finetuned-length_control_token is a machine learning model from convaise-idp. 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
11
4% of all-time downloads
All-time downloads
283
Public
Repo size
12.9 GB
Likes
0
Public
Click a slice to open those files.
.bin990 MB · 100%
From the Hugging Face model README
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:
This model was trained on a dataset called PWKP-GPT3-LENGTH-CONTROL-40BUCKETS. The dataset contains 30k instances taken from PWKP, then processed through GPT3 to obtain simplifications. The 30k instances come from: 10k which were supposed to generate very long simplifications, 10k which were supposed to generate very short simplifications, and 10k without specifying the simplicity level. The model does not sucessfuly work on these buckets. There exists another dataset, the PWKP-GPT3-LENGTH-CONTROL-4BUCKETS, but it was never trained on something. Those buckets are also rather unbalanced.
The idea comes from Controllable Sentence Simplification Louis Martin, https://arxiv.org/pdf/1910.02677.pdf
It was fine-tuned on the FLAN-T5-base model.
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Sacrebleu |
|---|---|---|---|---|
| 1.3257 | 1.0 | 1782 | 1.0906 | 15.4208 |
| 1.1718 | 2.0 | 3564 | 1.0648 | 15.5358 |
| 1.0972 | 3.0 | 5346 | 1.0484 | 15.8113 |
| 1.0472 | 4.0 | 7128 | 1.0394 | 16.0159 |
| 1.0092 | 5.0 | 8910 | 1.0305 | 16.1341 |
| 0.9858 | 6.0 | 10692 | 1.0276 | 16.2445 |