---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: phi_2_patent
  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. -->

# phi_2_patent

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: 0.9403
- Accuracy: 0.6678
- F1 Macro: 0.6213
- F1 Micro: 0.6678

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.9105        | 0.13  | 50   | 1.8338          | 0.3248   | 0.2207   | 0.3248   |
| 1.6023        | 0.26  | 100  | 1.6011          | 0.438    | 0.3087   | 0.438    |
| 1.4113        | 0.38  | 150  | 1.4239          | 0.4912   | 0.3599   | 0.4912   |
| 1.3062        | 0.51  | 200  | 1.2828          | 0.5498   | 0.4109   | 0.5498   |
| 1.2574        | 0.64  | 250  | 1.1801          | 0.5822   | 0.4702   | 0.5822   |
| 1.1687        | 0.77  | 300  | 1.1401          | 0.6032   | 0.4825   | 0.6032   |
| 1.1396        | 0.9   | 350  | 1.0853          | 0.613    | 0.5246   | 0.613    |
| 1.0529        | 1.02  | 400  | 1.0639          | 0.6226   | 0.5368   | 0.6226   |
| 1.0261        | 1.15  | 450  | 1.0742          | 0.6304   | 0.5449   | 0.6304   |
| 1.0068        | 1.28  | 500  | 1.0340          | 0.6444   | 0.5825   | 0.6444   |
| 0.975         | 1.41  | 550  | 1.0151          | 0.65     | 0.5777   | 0.65     |
| 0.966         | 1.53  | 600  | 1.0022          | 0.6498   | 0.5923   | 0.6498   |
| 1.0201        | 1.66  | 650  | 0.9899          | 0.6562   | 0.5854   | 0.6562   |
| 0.9346        | 1.79  | 700  | 0.9807          | 0.6598   | 0.5735   | 0.6598   |
| 0.9807        | 1.92  | 750  | 0.9694          | 0.6586   | 0.6004   | 0.6586   |
| 0.917         | 2.05  | 800  | 0.9664          | 0.6608   | 0.6086   | 0.6608   |
| 0.9268        | 2.17  | 850  | 0.9619          | 0.6626   | 0.6107   | 0.6626   |
| 1.0107        | 2.3   | 900  | 0.9548          | 0.6648   | 0.6156   | 0.6648   |
| 0.9378        | 2.43  | 950  | 0.9559          | 0.6656   | 0.6109   | 0.6656   |
| 0.9199        | 2.56  | 1000 | 0.9514          | 0.6658   | 0.6165   | 0.6658   |
| 0.8467        | 2.69  | 1050 | 0.9454          | 0.6714   | 0.6203   | 0.6714   |
| 0.8923        | 2.81  | 1100 | 0.9413          | 0.67     | 0.6206   | 0.67     |
| 0.9545        | 2.94  | 1150 | 0.9403          | 0.6678   | 0.6213   | 0.6678   |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2