---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
datasets:
- generator
model-index:
- name: cls_alldata_phi3_v1
  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. -->

# cls_alldata_phi3_v1

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 generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4956

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7566        | 0.0559 | 20   | 0.7643          |
| 0.6863        | 0.1117 | 40   | 0.7089          |
| 0.6538        | 0.1676 | 60   | 0.6706          |
| 0.6261        | 0.2235 | 80   | 0.6499          |
| 0.6402        | 0.2793 | 100  | 0.6321          |
| 0.594         | 0.3352 | 120  | 0.6226          |
| 0.5956        | 0.3911 | 140  | 0.6121          |
| 0.5743        | 0.4469 | 160  | 0.6016          |
| 0.5494        | 0.5028 | 180  | 0.5903          |
| 0.5861        | 0.5587 | 200  | 0.5887          |
| 0.5431        | 0.6145 | 220  | 0.5801          |
| 0.5404        | 0.6704 | 240  | 0.5746          |
| 0.5401        | 0.7263 | 260  | 0.5695          |
| 0.5363        | 0.7821 | 280  | 0.5644          |
| 0.5534        | 0.8380 | 300  | 0.5608          |
| 0.5936        | 0.8939 | 320  | 0.5552          |
| 0.5139        | 0.9497 | 340  | 0.5496          |
| 0.5096        | 1.0056 | 360  | 0.5468          |
| 0.4891        | 1.0615 | 380  | 0.5468          |
| 0.4524        | 1.1173 | 400  | 0.5433          |
| 0.4568        | 1.1732 | 420  | 0.5397          |
| 0.4462        | 1.2291 | 440  | 0.5374          |
| 0.4605        | 1.2849 | 460  | 0.5337          |
| 0.4469        | 1.3408 | 480  | 0.5328          |
| 0.458         | 1.3966 | 500  | 0.5313          |
| 0.4378        | 1.4525 | 520  | 0.5250          |
| 0.4654        | 1.5084 | 540  | 0.5232          |
| 0.4563        | 1.5642 | 560  | 0.5200          |
| 0.4664        | 1.6201 | 580  | 0.5155          |
| 0.4308        | 1.6760 | 600  | 0.5128          |
| 0.443         | 1.7318 | 620  | 0.5082          |
| 0.4508        | 1.7877 | 640  | 0.5070          |
| 0.4511        | 1.8436 | 660  | 0.4999          |
| 0.4467        | 1.8994 | 680  | 0.4996          |
| 0.4723        | 1.9553 | 700  | 0.4956          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1