---
library_name: peft
license: other
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: 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. -->

# lora

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 flock_task5_tranning dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7054

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.287         | 0.6897 | 10   | 1.4997          |
| 1.3264        | 1.3448 | 20   | 1.3904          |
| 0.9293        | 2.0    | 30   | 1.2929          |
| 1.2359        | 2.6897 | 40   | 1.2001          |
| 1.1123        | 3.3448 | 50   | 1.1125          |
| 0.8456        | 4.0    | 60   | 1.0130          |
| 0.92          | 4.6897 | 70   | 0.9277          |
| 0.9875        | 5.3448 | 80   | 0.8583          |
| 0.6225        | 6.0    | 90   | 0.8013          |
| 0.825         | 6.6897 | 100  | 0.7550          |
| 0.6775        | 7.3448 | 110  | 0.7281          |
| 0.6614        | 8.0    | 120  | 0.7120          |
| 0.6203        | 8.6897 | 130  | 0.7067          |
| 0.6521        | 9.3448 | 140  | 0.7054          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0