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---
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