---
base_model: google/flan-t5-large
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: flan-t5-large-field-short
  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-field-short

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: 0.3511
- Rouge1: 75.9188
- Rouge2: 65.0316
- Rougel: 74.1965
- Rougelsum: 74.2928
- Gen Len: 18.5368

## 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: 5e-05
- 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 225  | 0.4477          | 70.3244 | 54.48   | 67.539  | 67.5367   | 18.5368 |
| No log        | 2.0   | 450  | 0.3952          | 71.2109 | 55.6557 | 68.192  | 68.0612   | 18.4211 |
| 0.5212        | 3.0   | 675  | 0.3703          | 72.5832 | 59.067  | 70.4191 | 70.3352   | 18.4526 |
| 0.5212        | 4.0   | 900  | 0.3427          | 73.1074 | 58.472  | 70.4641 | 70.4554   | 18.4947 |
| 0.3084        | 5.0   | 1125 | 0.3303          | 74.4224 | 61.8209 | 72.1663 | 72.1812   | 18.5158 |
| 0.3084        | 6.0   | 1350 | 0.3265          | 74.6821 | 62.8891 | 72.8496 | 72.9381   | 18.4842 |
| 0.2453        | 7.0   | 1575 | 0.3250          | 74.8631 | 63.6981 | 73.088  | 73.0406   | 18.5789 |
| 0.2453        | 8.0   | 1800 | 0.3283          | 75.7529 | 64.1127 | 73.7844 | 73.6245   | 18.5158 |
| 0.2037        | 9.0   | 2025 | 0.3425          | 75.0953 | 63.3301 | 73.4542 | 73.4519   | 18.5053 |
| 0.2037        | 10.0  | 2250 | 0.3387          | 75.6678 | 64.5649 | 73.939  | 73.8801   | 18.5368 |
| 0.2037        | 11.0  | 2475 | 0.3343          | 75.2038 | 64.2915 | 73.673  | 73.5405   | 18.4947 |
| 0.1746        | 12.0  | 2700 | 0.3443          | 74.5103 | 62.7511 | 72.5728 | 72.5861   | 18.4947 |
| 0.1746        | 13.0  | 2925 | 0.3520          | 75.7764 | 64.4211 | 73.9112 | 73.9166   | 18.5368 |
| 0.1551        | 14.0  | 3150 | 0.3530          | 75.385  | 64.0909 | 73.6109 | 73.7228   | 18.5368 |
| 0.1551        | 15.0  | 3375 | 0.3511          | 75.9188 | 65.0316 | 74.1965 | 74.2928   | 18.5368 |


### Framework versions

- Transformers 4.43.2
- Pytorch 2.2.0a0+81ea7a4
- Datasets 2.20.0
- Tokenizers 0.19.1