---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0409MP1
  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. -->

# V0409MP1

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3404

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 20
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 6.1578        | 0.09  | 10   | 5.3816          |
| 5.3721        | 0.18  | 20   | 4.1461          |
| 3.968         | 0.27  | 30   | 2.7849          |
| 2.7382        | 0.36  | 40   | 1.8394          |
| 1.863         | 0.45  | 50   | 1.2646          |
| 1.3779        | 0.54  | 60   | 0.9405          |
| 1.0695        | 0.63  | 70   | 0.7297          |
| 0.8284        | 0.73  | 80   | 0.5808          |
| 0.6698        | 0.82  | 90   | 0.4740          |
| 0.5725        | 0.91  | 100  | 0.3968          |
| 0.4905        | 1.0   | 110  | 0.3449          |
| 0.4426        | 1.09  | 120  | 0.3412          |
| 0.4443        | 1.18  | 130  | 0.3411          |
| 0.4747        | 1.27  | 140  | 0.3409          |
| 0.4367        | 1.36  | 150  | 0.3408          |
| 0.4515        | 1.45  | 160  | 0.3408          |
| 0.4519        | 1.54  | 170  | 0.3407          |
| 0.4503        | 1.63  | 180  | 0.3405          |
| 0.4419        | 1.72  | 190  | 0.3405          |
| 0.4423        | 1.81  | 200  | 0.3404          |
| 0.4565        | 1.9   | 210  | 0.3404          |
| 0.4598        | 1.99  | 220  | 0.3404          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1