---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: fine-tuned_phi3.5
  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. -->

# fine-tuned_phi3.5

This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2392

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 6
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- training_steps: 100

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0244 | 10   | 1.4131          |
| No log        | 0.0487 | 20   | 1.3193          |
| 1.4022        | 0.0731 | 30   | 1.2778          |
| 1.4022        | 0.0975 | 40   | 1.2651          |
| 1.2145        | 0.1219 | 50   | 1.2546          |
| 1.2145        | 0.1462 | 60   | 1.2479          |
| 1.2145        | 0.1706 | 70   | 1.2449          |
| 1.1869        | 0.1950 | 80   | 1.2413          |
| 1.1869        | 0.2193 | 90   | 1.2402          |
| 1.2108        | 0.2437 | 100  | 1.2392          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.0.0+nv23.05
- Datasets 2.15.0
- Tokenizers 0.19.1