---
base_model: google/flan-t5-base
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: results
  results: []
pipeline_tag: text2text-generation
---

<!-- 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. -->

# results

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1507

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 16
- training_steps: 1698

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.0084        | 0.59  | 50   | 2.5425          |
| 2.7308        | 1.18  | 100  | 2.4483          |
| 2.6435        | 1.76  | 150  | 2.3925          |
| 2.5873        | 2.35  | 200  | 2.3558          |
| 2.5247        | 2.94  | 250  | 2.3276          |
| 2.5323        | 3.53  | 300  | 2.3003          |
| 2.4288        | 4.12  | 350  | 2.2771          |
| 2.4247        | 4.71  | 400  | 2.2659          |
| 2.4014        | 5.29  | 450  | 2.2439          |
| 2.3761        | 5.88  | 500  | 2.2336          |
| 2.3056        | 6.47  | 550  | 2.2236          |
| 2.3443        | 7.06  | 600  | 2.2182          |
| 2.2877        | 7.65  | 650  | 2.2066          |
| 2.3028        | 8.24  | 700  | 2.1953          |
| 2.2589        | 8.82  | 750  | 2.1958          |
| 2.2306        | 9.41  | 800  | 2.1834          |
| 2.2571        | 10.0  | 850  | 2.1826          |
| 2.2109        | 10.59 | 900  | 2.1782          |
| 2.2216        | 11.18 | 950  | 2.1802          |
| 2.1881        | 11.76 | 1000 | 2.1734          |
| 2.1794        | 12.35 | 1050 | 2.1691          |
| 2.1933        | 12.94 | 1100 | 2.1654          |
| 2.134         | 13.53 | 1150 | 2.1682          |
| 2.1698        | 14.12 | 1200 | 2.1564          |
| 2.1477        | 14.71 | 1250 | 2.1599          |
| 2.1353        | 15.29 | 1300 | 2.1573          |
| 2.1206        | 15.88 | 1350 | 2.1525          |
| 2.1175        | 16.47 | 1400 | 2.1520          |
| 2.1142        | 17.06 | 1450 | 2.1531          |
| 2.1152        | 17.65 | 1500 | 2.1529          |
| 2.1073        | 18.24 | 1550 | 2.1529          |
| 2.099         | 18.82 | 1600 | 2.1520          |
| 2.1061        | 19.41 | 1650 | 2.1507          |


### Framework versions

- PEFT 0.8.2
- Transformers 4.38.1
- Pytorch 2.3.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2