---
language:
- en
library_name: peft
tags:
- generated_from_trainer
datasets:
- GEM/viggo
base_model: microsoft/phi-2
model-index:
- name: phi-2
  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

This model is a fine-tuned version of [microsoftl](https://huggingface.co/microsoftl) on the GEM/viggo dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2330

## 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: 2.5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.917         | 0.04  | 50   | 1.4649          |
| 0.7037        | 0.08  | 100  | 0.4905          |
| 0.4209        | 0.12  | 150  | 0.3564          |
| 0.3534        | 0.16  | 200  | 0.3127          |
| 0.311         | 0.2   | 250  | 0.2940          |
| 0.2944        | 0.24  | 300  | 0.2798          |
| 0.2838        | 0.27  | 350  | 0.2710          |
| 0.2744        | 0.31  | 400  | 0.2634          |
| 0.2657        | 0.35  | 450  | 0.2577          |
| 0.2692        | 0.39  | 500  | 0.2513          |
| 0.263         | 0.43  | 550  | 0.2475          |
| 0.2664        | 0.47  | 600  | 0.2451          |
| 0.2535        | 0.51  | 650  | 0.2421          |
| 0.2594        | 0.55  | 700  | 0.2396          |
| 0.234         | 0.59  | 750  | 0.2379          |
| 0.2383        | 0.63  | 800  | 0.2361          |
| 0.2419        | 0.67  | 850  | 0.2350          |
| 0.2448        | 0.71  | 900  | 0.2337          |
| 0.241         | 0.74  | 950  | 0.2332          |
| 0.219         | 0.78  | 1000 | 0.2330          |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0