---
license: mit
tags:
- trl
- sft
- generated_from_trainer
base_model: microsoft/Phi-3-mini-128k-instruct
datasets:
- generator
model-index:
- name: phi-3-small-sft-lora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# phi-3-small-sft-lora

This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2964

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 128
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6299        | 1.0    | 1    | 1.2966          |
| 0.6065        | 1.9692 | 2    | 1.2964          |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1