---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan_vary_merged_5800_1
  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_vary_merged_5800_1

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1597
- Rouge1: 66.8856
- Rouge2: 55.6869
- Rougel: 63.8241
- Rougelsum: 66.7005
- Gen Len: 16.3392

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 11.8095       | 0.35  | 200  | 0.5275          | 38.2792 | 29.3331 | 37.9276 | 38.1283   | 8.0624  |
| 0.4481        | 0.7   | 400  | 0.3046          | 64.4437 | 52.3632 | 62.0225 | 64.2515   | 16.4262 |
| 0.3616        | 1.05  | 600  | 0.2656          | 64.9871 | 53.1185 | 62.4919 | 64.739    | 16.4279 |
| 0.2944        | 1.41  | 800  | 0.2412          | 65.2117 | 53.5512 | 62.6779 | 64.9318   | 16.4464 |
| 0.264         | 1.76  | 1000 | 0.2295          | 65.5748 | 54.0948 | 62.9803 | 65.3339   | 16.3866 |
| 0.2571        | 2.11  | 1200 | 0.2223          | 65.7216 | 53.793  | 62.9877 | 65.491    | 16.1898 |
| 0.2364        | 2.46  | 1400 | 0.2164          | 65.5444 | 53.9296 | 62.9975 | 65.3055   | 16.3172 |
| 0.2293        | 2.81  | 1600 | 0.2029          | 65.7977 | 54.3067 | 63.1851 | 65.5544   | 16.1766 |
| 0.2129        | 3.16  | 1800 | 0.2006          | 65.8342 | 53.9105 | 63.163  | 65.6175   | 16.1757 |
| 0.2184        | 3.51  | 2000 | 0.1931          | 65.1608 | 53.7707 | 62.6719 | 64.9743   | 16.1547 |
| 0.1952        | 3.87  | 2200 | 0.1873          | 66.3361 | 54.8382 | 63.2054 | 66.0954   | 16.3155 |
| 0.1992        | 4.22  | 2400 | 0.1847          | 66.316  | 55.0379 | 63.5154 | 66.0694   | 16.3594 |
| 0.1873        | 4.57  | 2600 | 0.1811          | 66.4999 | 55.263  | 63.8319 | 66.2513   | 16.3146 |
| 0.1839        | 4.92  | 2800 | 0.1783          | 66.0055 | 54.3406 | 62.9554 | 65.7387   | 16.3304 |
| 0.1748        | 5.27  | 3000 | 0.1777          | 66.1592 | 54.8048 | 63.407  | 66.0067   | 16.3348 |
| 0.1844        | 5.62  | 3200 | 0.1736          | 66.7642 | 55.3404 | 63.7069 | 66.5324   | 16.2996 |
| 0.1745        | 5.98  | 3400 | 0.1698          | 66.3946 | 55.1716 | 63.5596 | 66.1663   | 16.3216 |
| 0.1739        | 6.33  | 3600 | 0.1678          | 66.4472 | 55.1785 | 63.602  | 66.2704   | 16.3049 |
| 0.1633        | 6.68  | 3800 | 0.1680          | 66.6666 | 55.4584 | 63.8058 | 66.4708   | 16.3445 |
| 0.1659        | 7.03  | 4000 | 0.1682          | 66.6592 | 55.3712 | 63.5841 | 66.4587   | 16.2953 |
| 0.1557        | 7.38  | 4200 | 0.1634          | 66.876  | 55.423  | 63.8431 | 66.5569   | 16.2434 |
| 0.158         | 7.73  | 4400 | 0.1622          | 66.6165 | 55.2948 | 63.5996 | 66.4314   | 16.3849 |
| 0.1647        | 8.08  | 4600 | 0.1622          | 66.7592 | 55.5552 | 63.7194 | 66.5229   | 16.2794 |
| 0.1579        | 8.44  | 4800 | 0.1614          | 66.7889 | 55.5768 | 63.8266 | 66.5511   | 16.3181 |
| 0.1526        | 8.79  | 5000 | 0.1610          | 66.7516 | 55.5383 | 63.6509 | 66.5754   | 16.261  |
| 0.1506        | 9.14  | 5200 | 0.1608          | 66.9266 | 55.6277 | 63.7712 | 66.6668   | 16.3445 |
| 0.1502        | 9.49  | 5400 | 0.1604          | 66.9759 | 55.6586 | 63.8856 | 66.7849   | 16.3251 |
| 0.158         | 9.84  | 5600 | 0.1597          | 66.8856 | 55.6869 | 63.8241 | 66.7005   | 16.3392 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.14.0