---
language:
- it
tags:
- summarization
datasets:
- ARTeLab/ilpost
metrics:
- rouge
base_model: gsarti/it5-base
model-index:
- name: summarization_ilpost
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: medical_questions_pairs
      type: medical_questions_pairs
      config: default
      split: train
    metrics:
    - type: rouge
      value: 12.5087
      name: ROUGE-1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTk1NzM4NjEyYjlkOWQ3Yzk0NjNiNDYzZjIwNDZkYWFlYzJlNTA4ZThiNjEzYWQzZWVjYzVmNTYyNjlhMjgzOCIsInZlcnNpb24iOjF9.v6mtEtzUqnUfSBwZu-vXDJmuVGvj4IvSgUFjdWy1RX9ShaC0TtNZJ20W4zjrEZ26Xmk7uqC51hK5ya6kx11WDQ
    - type: rouge
      value: 3.6796
      name: ROUGE-2
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMWQ4YWRmZGVjZTk5YTdjYzZhNzNkZDBmOTRmMzVmODY4OGU4MjI5OTdmZGQ3MTRjNDBmYTBkMTE0MzQ4ZDQ5YSIsInZlcnNpb24iOjF9.Ux7-ReB2i0MLurwxzzOmIi6dGUCUeZNYXgnGX4f8MTVJBMeMFMRFsG3Im1j0-DnpIxuvXETc8J6eZ5PR_5nIAg
    - type: rouge
      value: 11.0954
      name: ROUGE-L
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjRkZTYyYjRhNTNlMThkZjI3ZmE3MmNlOTFiMmQ0MGRhMTE3ZWM5ODk1OWRkZThiYTFiNDg5MjE2ODVhM2QyNyIsInZlcnNpb24iOjF9.yucLivteb6CxBBMZ1gydBhiWPBzwL2Ga9OS37z0o0tuPSWHjbsZtoVTzrHuJcjH-kwnR_QNA1AWokSf9grs4BQ
    - type: rouge
      value: 11.5897
      name: ROUGE-LSUM
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDI4ZmYxOWQzOTcyNGIyMWM2NGU4MzM0ZWI1MjRkN2ExNzFmNDFlNzI4ZTI4M2NkYzY5MmQ4MDgxZjhjMDExMyIsInZlcnNpb24iOjF9.riA7X5EfOrBirLWMyOYS5UWReNAm1sjrAPihNuW4lx0IzKdafZ3bUJrH1QNojae5p_XP8AyU8yygZ7TQgN2gBw
    - type: loss
      value: 3.0159499645233154
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzhmYzJlMWYwYTM2OGFlNjQ2YjkxYWI1YzNkOTRjMjI0NGQ2ZTNhYjUzN2RhMDQxMjI1NWUyYjgwNTYzN2RkNiIsInZlcnNpb24iOjF9.I_CHEnSn61amBXNSOqBXSkGL09fvRv700bHyC41vNowaBUNtO5vOabRfhYi0IuPmsEI8eh_IEVrwNpbTgdtlAg
    - type: gen_len
      value: 18.9961
      name: gen_len
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOWU5NDBkZDMyNWJjN2NkYWEyNGZjOGY5MDQyOTVmN2I5MTVhMTk0N2I5YjIxZjI4YmY0MmRmZmU3YWIzMGRiYSIsInZlcnNpb24iOjF9.GC80tSpC8-wSuuzGc8wG9iDeSZ6CU1gdczoLiYEFdz-JfCrZa82UGr0EHXTzbaPKjb2Di1MyeH77hygu5BJpCQ
---

# summarization_ilpost

This model is a fine-tuned version of [gsarti/it5-base](https://huggingface.co/gsarti/it5-base) on IlPost dataset for Abstractive Summarization.

It achieves the following results:
- Loss: 1.6020
- Rouge1: 33.7802
- Rouge2: 16.2953
- Rougel: 27.4797
- Rougelsum: 30.2273
- Gen Len: 45.3175

## Usage 

```python
from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("ARTeLab/it5-summarization-ilpost")
model = T5ForConditionalGeneration.from_pretrained("ARTeLab/it5-summarization-ilpost")
```

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4.0

### Framework versions
- Transformers 4.12.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3