---
library_name: peft
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
model-index:
- name: flan-t5-small-LORA
  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-t5-small-LORA

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan

## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.2   | 100  | nan             |
| No log        | 0.4   | 200  | nan             |
| No log        | 0.6   | 300  | nan             |
| No log        | 0.8   | 400  | nan             |
| 0.0           | 1.0   | 500  | nan             |
| 0.0           | 1.2   | 600  | nan             |
| 0.0           | 1.4   | 700  | nan             |
| 0.0           | 1.6   | 800  | nan             |
| 0.0           | 1.8   | 900  | nan             |
| 0.0           | 2.0   | 1000 | nan             |
| 0.0           | 2.2   | 1100 | nan             |
| 0.0           | 2.4   | 1200 | nan             |
| 0.0           | 2.6   | 1300 | nan             |
| 0.0           | 2.8   | 1400 | nan             |
| 0.0           | 3.0   | 1500 | nan             |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3