---
base_model: google/flan-t5-base
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: phi-3-mini-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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dhanishetty-personaluse/huggingface/runs/1ojupjbx)
# phi-3-mini-LoRA

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0702

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.6034        | 0.1688 | 50   | 1.3534          |
| 1.44          | 0.3376 | 100  | 1.2534          |
| 1.39          | 0.5063 | 150  | 1.2045          |
| 1.3075        | 0.6751 | 200  | 1.1710          |
| 1.2984        | 0.8439 | 250  | 1.1482          |
| 1.2933        | 1.0127 | 300  | 1.1500          |
| 1.2286        | 1.1814 | 350  | 1.1385          |
| 1.206         | 1.3502 | 400  | 1.1237          |
| 1.2097        | 1.5190 | 450  | 1.1112          |
| 1.1982        | 1.6878 | 500  | 1.1074          |
| 1.2451        | 1.8565 | 550  | 1.0894          |
| 1.1447        | 2.0253 | 600  | 1.1006          |
| 1.1324        | 2.1941 | 650  | 1.0787          |
| 1.137         | 2.3629 | 700  | 1.0798          |
| 1.14          | 2.5316 | 750  | 1.0739          |
| 1.1112        | 2.7004 | 800  | 1.0694          |
| 1.1436        | 2.8692 | 850  | 1.0702          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.43.2
- Pytorch 2.1.0
- Datasets 2.20.0
- Tokenizers 0.19.1