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---
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: 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 |