---
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: 2.6519

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2568        | 0.59  | 50   | 2.9764          |
| 3.2186        | 1.18  | 100  | 2.9349          |
| 3.1884        | 1.76  | 150  | 2.8820          |
| 3.1448        | 2.35  | 200  | 2.8404          |
| 3.1166        | 2.94  | 250  | 2.8120          |
| 3.0742        | 3.53  | 300  | 2.7899          |
| 3.0662        | 4.12  | 350  | 2.7724          |
| 3.0379        | 4.71  | 400  | 2.7578          |
| 3.0301        | 5.29  | 450  | 2.7457          |
| 3.0071        | 5.88  | 500  | 2.7352          |
| 3.0084        | 6.47  | 550  | 2.7259          |
| 2.9632        | 7.06  | 600  | 2.7177          |
| 2.9706        | 7.65  | 650  | 2.7104          |
| 2.9543        | 8.24  | 700  | 2.7037          |
| 2.9573        | 8.82  | 750  | 2.6979          |
| 2.9663        | 9.41  | 800  | 2.6928          |
| 2.9243        | 10.0  | 850  | 2.6877          |
| 2.9451        | 10.59 | 900  | 2.6832          |
| 2.9027        | 11.18 | 950  | 2.6790          |
| 2.9255        | 11.76 | 1000 | 2.6754          |
| 2.916         | 12.35 | 1050 | 2.6719          |
| 2.9155        | 12.94 | 1100 | 2.6688          |
| 2.9223        | 13.53 | 1150 | 2.6659          |
| 2.9141        | 14.12 | 1200 | 2.6635          |
| 2.8931        | 14.71 | 1250 | 2.6612          |
| 2.8988        | 15.29 | 1300 | 2.6590          |
| 2.8986        | 15.88 | 1350 | 2.6573          |
| 2.8998        | 16.47 | 1400 | 2.6558          |
| 2.9004        | 17.06 | 1450 | 2.6546          |
| 2.9036        | 17.65 | 1500 | 2.6535          |
| 2.885         | 18.24 | 1550 | 2.6528          |
| 2.8994        | 18.82 | 1600 | 2.6522          |
| 2.8971        | 19.41 | 1650 | 2.6519          |


### Framework versions

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