---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: phi_2_twitter
  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_twitter

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: 0.5104
- Accuracy: 0.7647
- F1 Macro: 0.7172
- F1 Micro: 0.7647

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.5921        | 0.18  | 50   | 0.6037          | 0.6958   | 0.5054   | 0.6958   |
| 0.5904        | 0.37  | 100  | 0.5537          | 0.7188   | 0.6277   | 0.7188   |
| 0.5021        | 0.55  | 150  | 0.6041          | 0.7160   | 0.5774   | 0.7160   |
| 0.5266        | 0.74  | 200  | 0.5544          | 0.7096   | 0.6496   | 0.7096   |
| 0.5427        | 0.92  | 250  | 0.5331          | 0.7399   | 0.6915   | 0.7399   |
| 0.4715        | 1.1   | 300  | 0.5436          | 0.7399   | 0.6361   | 0.7399   |
| 0.4829        | 1.29  | 350  | 0.5217          | 0.7564   | 0.7135   | 0.7564   |
| 0.4676        | 1.47  | 400  | 0.5225          | 0.7537   | 0.6829   | 0.7537   |
| 0.5196        | 1.65  | 450  | 0.5163          | 0.7629   | 0.7096   | 0.7629   |
| 0.4815        | 1.84  | 500  | 0.5213          | 0.7656   | 0.7215   | 0.7656   |
| 0.4836        | 2.02  | 550  | 0.5221          | 0.7619   | 0.7191   | 0.7619   |
| 0.4945        | 2.21  | 600  | 0.5134          | 0.7638   | 0.7173   | 0.7638   |
| 0.4103        | 2.39  | 650  | 0.5125          | 0.7684   | 0.7211   | 0.7684   |
| 0.4191        | 2.57  | 700  | 0.5108          | 0.7684   | 0.7226   | 0.7684   |
| 0.5004        | 2.76  | 750  | 0.5104          | 0.7647   | 0.7172   | 0.7647   |
| 0.4398        | 2.94  | 800  | 0.5114          | 0.7675   | 0.7138   | 0.7675   |


### Framework versions

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