---
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: cnn_dailymail
      type: cnn_dailymail
      config: 3.0.0
      split: test
    metrics:
    - type: rouge
      value: 11.9376
      name: ROUGE-1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2Q2MTU4ZjRjOTAwMjg1NGFlZTU5MjUzZWE3YjJmNjdiMjViMTM3NzYxNzM4ODFiYjQwOTg5MGU0NzhhMjIyOSIsInZlcnNpb24iOjF9.Z624zCBuYlYNnmAEd-QA62tAocs465KGwxIyDUea5BkI4H0A9EFtYIP6oQ4DZ3NyojQN6G54EWlsBP0BSpgRAg
    - type: rouge
      value: 3.5381
      name: ROUGE-2
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiN2VmMzcyZDY2YjY0N2ZhZjM2OTMxMWQyMzU0OWM3NDliYWRjMDNjOGZhN2E0OTU2Mjk2YWRiNzVjZGRkMTZkMiIsInZlcnNpb24iOjF9.7Cdh7ubB8enekUMDaGlYZnX02CglrpvWKG9fYFzW1l-VlWQQbsDovIHOBqNnVSJGCtmCIqJfT2Q9Zp85oM96CA
    - type: rouge
      value: 9.9611
      name: ROUGE-L
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTdkODMzODdkNjExNjhhOGEyYzdlYTYyNTAwMTcwYzJmZWUyMThiMDJiZTc1Mjc4NjJhZjBkMjU2OWI3NWMxOCIsInZlcnNpb24iOjF9.z5yc8v8DHXB6plgwFRS34n85X78t9VNvufpjZ1OdEorm3wnf8_sZyhF_rXwSZ_fbG9uH0Qcf8o5JjCOvHBs0AQ
    - type: rouge
      value: 11.2146
      name: ROUGE-LSUM
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzhlNmIzYWY4MWYxMWEyOGE3ZWY0MGFkMGQ1M2VhYjM3ZjczNzg4NzRkZDkwYzZhMWMyZThmMTIwNzYyZDMxYiIsInZlcnNpb24iOjF9.eLS5vE1lSyOF_YWwdb3ARQp4zaiTX9iwzvSqLLcdCg0tSMb4kwAjRD2tTxq5hJ2P-_ZzjbykaX7n7syOpO6ODw
    - type: loss
      value: 8.635225296020508
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZGYyZjYzZWZiYzIzNmI0NTEzNGYxNDljODFkMjE1Yzk1NzI2ZDcwYjYzNGVlZjc4NDc0NGM5ZjM2OTgwY2ExMSIsInZlcnNpb24iOjF9.D-g1NamsmrDUgcA20CQ57Mj9tHdQ5bpIjWuGtIy5ZQh_GBN5UN9wWslzm7mYEuPNWwzITR8fMtdBOLJv8xVABA
    - type: gen_len
      value: 18.9985
      name: gen_len
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzcyMmY4ODg3ZTdmOTc4NmRjYTc4MGI0NjBhYmFhMDc4NWUyNWVkMzI1NjU0MzE5MGNhODEyM2IyM2UxNzU4NSIsInZlcnNpb24iOjF9.mWqGs_wVk9CyBkYczl5sJp6YURbGzHE6tx_KNjpRIaF4B-8YfyM9pjrl_Q8kfPGrnPgLrJrURGC26Bza9kYUCw
---

# 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