---
base_model: google/flan-t5-base
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: results
  results: []
pipeline_tag: text-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: 1.9615

## 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: 6
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 23
- training_steps: 2373

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.0035        | 0.42  | 50   | 2.5115          |
| 2.7023        | 0.84  | 100  | 2.3978          |
| 2.6198        | 1.26  | 150  | 2.3258          |
| 2.5523        | 1.68  | 200  | 2.2768          |
| 2.4817        | 2.1   | 250  | 2.2360          |
| 2.4591        | 2.52  | 300  | 2.2041          |
| 2.4           | 2.94  | 350  | 2.1844          |
| 2.3709        | 3.36  | 400  | 2.1547          |
| 2.3591        | 3.78  | 450  | 2.1366          |
| 2.3232        | 4.2   | 500  | 2.1210          |
| 2.3016        | 4.62  | 550  | 2.1119          |
| 2.3041        | 5.04  | 600  | 2.0993          |
| 2.2646        | 5.46  | 650  | 2.0908          |
| 2.247         | 5.88  | 700  | 2.0794          |
| 2.1935        | 6.3   | 750  | 2.0612          |
| 2.2334        | 6.72  | 800  | 2.0573          |
| 2.2054        | 7.14  | 850  | 2.0498          |
| 2.212         | 7.56  | 900  | 2.0460          |
| 2.1687        | 7.98  | 950  | 2.0388          |
| 2.1454        | 8.4   | 1000 | 2.0347          |
| 2.1344        | 8.82  | 1050 | 2.0243          |
| 2.1522        | 9.24  | 1100 | 2.0155          |
| 2.1051        | 9.66  | 1150 | 2.0144          |
| 2.1435        | 10.08 | 1200 | 2.0152          |
| 2.1251        | 10.5  | 1250 | 2.0133          |
| 2.0664        | 10.92 | 1300 | 2.0000          |
| 2.0656        | 11.34 | 1350 | 2.0002          |
| 2.1186        | 11.76 | 1400 | 1.9933          |
| 2.0719        | 12.18 | 1450 | 1.9906          |
| 2.0389        | 12.61 | 1500 | 1.9913          |
| 2.0655        | 13.03 | 1550 | 1.9874          |
| 2.0371        | 13.45 | 1600 | 1.9824          |
| 2.0581        | 13.87 | 1650 | 1.9789          |
| 2.0068        | 14.29 | 1700 | 1.9801          |
| 2.0536        | 14.71 | 1750 | 1.9750          |
| 2.0311        | 15.13 | 1800 | 1.9729          |
| 2.0292        | 15.55 | 1850 | 1.9716          |
| 1.9955        | 15.97 | 1900 | 1.9714          |
| 2.0056        | 16.39 | 1950 | 1.9671          |
| 2.0391        | 16.81 | 2000 | 1.9642          |
| 2.0059        | 17.23 | 2050 | 1.9687          |
| 2.0155        | 17.65 | 2100 | 1.9644          |
| 1.9745        | 18.07 | 2150 | 1.9617          |
| 1.9929        | 18.49 | 2200 | 1.9621          |
| 1.9978        | 18.91 | 2250 | 1.9639          |
| 2.023         | 19.33 | 2300 | 1.9617          |
| 1.992         | 19.75 | 2350 | 1.9615          |


### Framework versions

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