---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-large-extraction-cnndm_4000-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_4000-all

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8084
- Rouge1: 35.2389
- Rouge2: 15.2731
- Rougel: 29.9899
- Rougelsum: 30.0262
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.2214        | 0.4   | 200  | 1.9330          | 34.7186 | 15.2527 | 29.7852 | 29.8623   | 19.0    |
| 1.2119        | 0.8   | 400  | 1.9119          | 34.718  | 15.3471 | 29.4347 | 29.4709   | 19.0    |
| 1.1482        | 1.2   | 600  | 2.0060          | 34.1536 | 15.0233 | 29.503  | 29.518    | 18.99   |
| 1.1102        | 1.6   | 800  | 2.0276          | 34.8004 | 15.1277 | 29.5782 | 29.6371   | 18.998  |
| 1.1295        | 2.0   | 1000 | 1.9375          | 35.1942 | 15.2087 | 30.156  | 30.0925   | 18.996  |
| 1.2045        | 2.4   | 1200 | 1.9016          | 35.5121 | 15.8033 | 30.515  | 30.5451   | 18.984  |
| 1.492         | 2.8   | 1400 | 1.8119          | 35.0575 | 15.2373 | 29.8621 | 29.9106   | 19.0    |
| 1.4535        | 3.2   | 1600 | 1.8160          | 35.0796 | 15.6135 | 30.1449 | 30.189    | 19.0    |
| 1.4087        | 3.6   | 1800 | 1.8223          | 34.9121 | 15.3203 | 29.7578 | 29.8006   | 18.998  |
| 1.4098        | 4.0   | 2000 | 1.8084          | 35.2389 | 15.2731 | 29.9899 | 30.0262   | 19.0    |
| 1.3759        | 4.4   | 2200 | 1.8357          | 35.4492 | 15.8883 | 30.1135 | 30.151    | 19.0    |
| 1.3565        | 4.8   | 2400 | 1.8347          | 34.6559 | 15.2567 | 29.5659 | 29.5704   | 19.0    |
| 1.3268        | 5.2   | 2600 | 1.8416          | 35.326  | 15.5918 | 29.841  | 29.8391   | 19.0    |
| 1.3204        | 5.6   | 2800 | 1.8445          | 35.4671 | 15.5422 | 30.169  | 30.1985   | 19.0    |
| 1.3271        | 6.0   | 3000 | 1.8374          | 35.4057 | 15.6566 | 30.2378 | 30.2328   | 18.998  |


### Framework versions

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