---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-large-extraction-cnndm_10000-all
  results: []
---

<!-- 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. -->

# flan-t5-large-extraction-cnndm_10000-all

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7044
- Rouge1: 34.8618
- Rouge2: 15.5978
- Rougel: 29.7948
- Rougelsum: 29.7581
- Gen Len: 19.0

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 24
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.1668        | 0.16  | 200  | 1.8280          | 33.7941 | 14.3114 | 28.7743 | 28.7968   | 19.0    |
| 1.9736        | 0.32  | 400  | 1.7818          | 34.8351 | 15.5548 | 29.8974 | 29.8557   | 18.99   |
| 1.904         | 0.48  | 600  | 1.7513          | 35.465  | 15.8566 | 30.7139 | 30.6596   | 18.986  |
| 1.8938        | 0.64  | 800  | 1.7440          | 34.6193 | 15.5473 | 30.0661 | 30.0019   | 18.99   |
| 1.8471        | 0.8   | 1000 | 1.7366          | 34.553  | 15.2214 | 29.8807 | 29.8419   | 18.99   |
| 1.8621        | 0.96  | 1200 | 1.7486          | 34.9309 | 15.1932 | 29.8973 | 29.8774   | 18.99   |
| 1.8082        | 1.12  | 1400 | 1.7311          | 35.3395 | 16.0976 | 30.2748 | 30.293    | 18.99   |
| 1.7448        | 1.28  | 1600 | 1.7155          | 35.1387 | 15.7462 | 29.924  | 29.9287   | 18.99   |
| 1.7655        | 1.44  | 1800 | 1.7239          | 35.3603 | 15.6355 | 30.3944 | 30.3766   | 19.0    |
| 1.7283        | 1.6   | 2000 | 1.7132          | 34.7368 | 15.4073 | 29.9027 | 29.8971   | 19.0    |
| 1.7463        | 1.76  | 2200 | 1.7171          | 35.0545 | 15.726  | 30.0364 | 30.0056   | 19.0    |
| 1.7462        | 1.92  | 2400 | 1.7044          | 34.8618 | 15.5978 | 29.7948 | 29.7581   | 19.0    |
| 1.719         | 2.08  | 2600 | 1.7285          | 34.9598 | 15.5237 | 29.5593 | 29.5803   | 19.0    |
| 1.6828        | 2.24  | 2800 | 1.7179          | 35.0944 | 15.7333 | 29.8381 | 29.7784   | 19.0    |
| 1.7           | 2.4   | 3000 | 1.7047          | 35.1766 | 15.7758 | 29.818  | 29.7859   | 19.0    |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.5.1
- Tokenizers 0.12.1