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---
library_name: peft
license: mit
base_model: microsoft/phi-2
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 15d56899-41e5-46be-9482-e05c51fc9787
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<br>

# 15d56899-41e5-46be-9482-e05c51fc9787

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6424

## 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: 0.000214
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0000 | 1    | 0.7124          |
| 0.7606        | 0.0021 | 50   | 0.7107          |
| 0.7933        | 0.0042 | 100  | 0.8085          |
| 0.8646        | 0.0063 | 150  | 0.8180          |
| 0.8118        | 0.0084 | 200  | 0.6951          |
| 0.7386        | 0.0105 | 250  | 0.6735          |
| 0.7899        | 0.0126 | 300  | 0.6701          |
| 0.7901        | 0.0148 | 350  | 0.6612          |
| 0.7539        | 0.0169 | 400  | 0.6434          |
| 0.7689        | 0.0190 | 450  | 0.6437          |
| 0.737         | 0.0211 | 500  | 0.6424          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1