---
base_model: microsoft/Phi-3-mini-4k-instruct
datasets:
- generator
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: ERC_SUMMARY_phi3_peft
  results: []
---

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[<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/gladys-vimalan-anna-university/ERC_PEFT_phi3/runs/kz79um3z)
# ERC_SUMMARY_phi3_peft

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the ArunaMak/ERC_summary dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3262

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4928        | 1.0   | 21   | 1.4815          |
| 1.3604        | 2.0   | 42   | 1.3828          |
| 1.3606        | 3.0   | 63   | 1.3482          |
| 1.3651        | 4.0   | 84   | 1.3323          |
| 1.3101        | 5.0   | 105  | 1.3271          |
| 1.2846        | 6.0   | 126  | 1.3262          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.43.0.dev0
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1