---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-large-extraction-cnndm_20000-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_20000-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: 1.6652
- Rouge1: 35.487
- Rouge2: 15.6713
- Rougel: 29.9519
- Rougelsum: 29.9368
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.1295        | 0.08  | 200  | 1.8266          | 34.0465 | 14.7511 | 29.3395 | 29.3437   | 19.0    |
| 1.9354        | 0.16  | 400  | 1.7732          | 34.7923 | 15.3094 | 29.8484 | 29.8757   | 18.99   |
| 1.854         | 0.24  | 600  | 1.7367          | 34.8358 | 15.1969 | 29.9971 | 30.0064   | 18.986  |
| 1.833         | 0.32  | 800  | 1.7120          | 34.7854 | 15.5144 | 29.8141 | 29.7863   | 18.982  |
| 1.8217        | 0.4   | 1000 | 1.7256          | 34.7274 | 15.2763 | 30.0298 | 30.0871   | 19.0    |
| 1.8309        | 0.48  | 1200 | 1.7089          | 35.4328 | 15.7724 | 30.0655 | 30.0199   | 19.0    |
| 1.825         | 0.56  | 1400 | 1.6947          | 35.4116 | 15.6911 | 30.1438 | 30.1764   | 19.0    |
| 1.7914        | 0.64  | 1600 | 1.7119          | 35.5918 | 16.3762 | 30.3234 | 30.2807   | 19.0    |
| 1.7889        | 0.72  | 1800 | 1.6810          | 35.6413 | 15.8936 | 30.2848 | 30.2291   | 19.0    |
| 1.7576        | 0.8   | 2000 | 1.6826          | 35.9424 | 15.6803 | 30.5998 | 30.5571   | 19.0    |
| 1.7763        | 0.88  | 2200 | 1.6748          | 35.7543 | 15.984  | 30.7197 | 30.721    | 18.998  |
| 1.7604        | 0.96  | 2400 | 1.6652          | 35.487  | 15.6713 | 29.9519 | 29.9368   | 19.0    |
| 1.7138        | 1.04  | 2600 | 1.6860          | 36.0333 | 16.4065 | 30.7249 | 30.7168   | 19.0    |
| 1.6951        | 1.12  | 2800 | 1.6792          | 35.3149 | 15.7178 | 30.1555 | 30.1517   | 18.998  |
| 1.6752        | 1.2   | 3000 | 1.6832          | 34.7566 | 15.4179 | 29.7687 | 29.8259   | 19.0    |


### Framework versions

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