---
license: mit
tags:
- generated_from_trainer
datasets:
- it5/datasets
metrics:
- rouge
model-index:
- name: it5-efficient-small-el32-qa-0.0003
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: it5/datasets qa
      type: it5/datasets
      args: qa
    metrics:
    - name: Rouge1
      type: rouge
      value: 74.2234
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# it5-efficient-small-el32-qa-0.0003

This model is a fine-tuned version of [stefan-it/it5-efficient-small-el32](https://huggingface.co/stefan-it/it5-efficient-small-el32) on the it5/datasets qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8225
- Rouge1: 74.2234
- Rouge2: 40.5909
- Rougel: 74.1327
- Rougelsum: 74.2081
- Gen Len: 4.7055

## 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: 0.0003
- 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: 7.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.1164        | 0.8   | 5000  | 0.8244          | 66.4678 | 35.3554 | 66.4543 | 66.4522   | 4.541   |
| 0.9097        | 1.59  | 10000 | 0.7299          | 70.0574 | 37.5535 | 69.9512 | 70.0084   | 4.5548  |
| 0.6637        | 2.39  | 15000 | 0.7314          | 72.0767 | 39.2263 | 72.0257 | 72.0473   | 4.703   |
| 0.5015        | 3.19  | 20000 | 0.7147          | 73.0185 | 39.9998 | 72.9347 | 72.9576   | 4.75    |
| 0.5101        | 3.99  | 25000 | 0.7055          | 73.7898 | 40.5481 | 73.7235 | 73.7901   | 4.8728  |
| 0.3903        | 4.78  | 30000 | 0.7442          | 74.0845 | 39.9841 | 74.0172 | 74.0635   | 4.5938  |
| 0.2993        | 5.58  | 35000 | 0.8184          | 73.8405 | 40.2569 | 73.7756 | 73.7972   | 4.7412  |
| 0.2227        | 6.38  | 40000 | 0.8278          | 74.0159 | 40.6403 | 73.9412 | 73.9722   | 4.742   |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3