---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: phi_2_scotus
  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_scotus

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: 2.0717
- Accuracy: 0.3557
- F1 Macro: 0.1359
- F1 Micro: 0.3557

## 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.5187        | 0.32  | 50   | 2.4656          | 0.2171   | 0.0941   | 0.2171   |
| 2.2348        | 0.64  | 100  | 2.3156          | 0.2579   | 0.0980   | 0.2579   |
| 2.2023        | 0.96  | 150  | 2.2223          | 0.2914   | 0.1103   | 0.2914   |
| 2.1145        | 1.27  | 200  | 2.1800          | 0.3064   | 0.1139   | 0.3064   |
| 1.993         | 1.59  | 250  | 2.1359          | 0.3179   | 0.1254   | 0.3179   |
| 1.9609        | 1.91  | 300  | 2.1034          | 0.3457   | 0.1345   | 0.3457   |
| 2.0137        | 2.23  | 350  | 2.1008          | 0.3564   | 0.1382   | 0.3564   |
| 1.9418        | 2.55  | 400  | 2.0717          | 0.3557   | 0.1359   | 0.3557   |
| 1.8887        | 2.87  | 450  | 2.0744          | 0.3636   | 0.1442   | 0.3636   |


### Framework versions

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