---
tags:
- generated_from_trainer
datasets:
- jsonl_dataset_sum.py
metrics:
- rouge
model-index:
- name: summarization_all
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: jsonl_dataset_sum.py
      type: jsonl_dataset_sum.py
      config: 'null'
      split: None
    metrics:
    - name: Rouge1
      type: rouge
      value: 21.9857
---

<!-- 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. -->

# summarization_all

This model is a fine-tuned version of [KETI-AIR/long-ke-t5-base](https://huggingface.co/KETI-AIR/long-ke-t5-base) on the jsonl_dataset_sum.py dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1442
- Rouge1: 21.9857
- Rouge2: 10.2876
- Rougel: 21.4026
- Rougelsum: 21.4278
- Gen Len: 86.2560

## 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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step    | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.2503        | 1.0   | 184670  | 1.2439          | 20.2525 | 9.1467  | 19.7454 | 19.771    | 87.1766 |
| 1.1629        | 2.0   | 369340  | 1.1773          | 21.0068 | 9.6691  | 20.4565 | 20.4888   | 89.6074 |
| 1.1087        | 3.0   | 554010  | 1.1431          | 21.0216 | 9.6545  | 20.489  | 20.5108   | 85.5895 |
| 1.056         | 4.0   | 738680  | 1.1247          | 21.6776 | 10.1424 | 21.09   | 21.1168   | 89.6576 |
| 1.0199        | 5.0   | 923350  | 1.1179          | 21.6563 | 10.0965 | 21.0814 | 21.1056   | 89.2454 |
| 0.9652        | 6.0   | 1108020 | 1.1122          | 21.6209 | 10.0725 | 21.0623 | 21.0864   | 86.7079 |
| 0.92          | 7.0   | 1292690 | 1.1136          | 21.9396 | 10.2734 | 21.3465 | 21.3745   | 86.5547 |
| 0.8804        | 8.0   | 1477360 | 1.1228          | 21.8457 | 10.1858 | 21.2552 | 21.278    | 87.6413 |
| 0.8447        | 9.0   | 1662030 | 1.1327          | 21.92   | 10.2635 | 21.3415 | 21.3633   | 86.4453 |
| 0.7678        | 10.0  | 1846700 | 1.1442          | 21.9857 | 10.2876 | 21.4026 | 21.4278   | 86.2560 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.0
- Datasets 2.8.0
- Tokenizers 0.13.2