---
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
metrics:
- rouge
- f1
- recall
- precision
model-index:
- name: KGAQ-2
  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. -->

# KGAQ-2

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6712
- Rouge1: 9.9002
- Rouge2: 0.817
- Rougel: 9.31
- Rougelsum: 9.8757
- Gen Len: 4.0
- F1: 0.0005
- Recall: 0.0008
- Precision: 0.0003

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|:------:|:------:|:---------:|
| 3.5701        | 1.0   | 598  | 3.3914          | 14.1052 | 1.2078 | 13.0257 | 14.1332   | 3.0     | 0.0    | 0.0    | 0.0       |
| 3.0379        | 2.0   | 1196 | 2.7468          | 12.4379 | 1.0435 | 11.3645 | 12.4814   | 3.0     | 0.0005 | 0.0008 | 0.0003    |
| 2.2773        | 3.0   | 1794 | 2.4962          | 25.6591 | 2.6653 | 16.5422 | 25.687    | 6.0     | 0.0    | 0.0    | 0.0       |
| 1.8845        | 4.0   | 2392 | 2.4370          | 8.8131  | 0.2887 | 8.1866  | 8.8014    | 3.0     | 0.0005 | 0.0008 | 0.0003    |
| 1.7721        | 5.0   | 2990 | 2.5342          | 8.2864  | 0.5105 | 7.6569  | 8.2655    | 3.0     | 0.0005 | 0.0008 | 0.0003    |
| 2.1007        | 6.0   | 3588 | 2.5028          | 27.8343 | 3.8693 | 19.0586 | 27.8325   | 6.4795  | 0.0022 | 0.0036 | 0.0015    |
| 2.0255        | 7.0   | 4186 | 2.5544          | 8.2864  | 0.5105 | 7.6569  | 8.2655    | 3.0     | 0.0005 | 0.0008 | 0.0003    |
| 1.9177        | 8.0   | 4784 | 2.5356          | 22.6347 | 3.1887 | 14.2667 | 22.6751   | 7.0     | 0.0005 | 0.0008 | 0.0003    |
| 1.7165        | 9.0   | 5382 | 2.5492          | 9.9002  | 0.817  | 9.31    | 9.8757    | 4.0     | 0.0005 | 0.0008 | 0.0003    |
| 1.645         | 10.0  | 5980 | 2.6712          | 9.9002  | 0.817  | 9.31    | 9.8757    | 4.0     | 0.0005 | 0.0008 | 0.0003    |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1