---
license: mit
library_name: peft
tags:
- generated_from_trainer
datasets:
- viggo
base_model: microsoft/phi-2
model-index:
- name: phi2-viggo-finetune
  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. -->

# phi2-viggo-finetune

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the viggo dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2331

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9356        | 0.04  | 50   | 1.4822          |
| 0.7214        | 0.08  | 100  | 0.5014          |
| 0.4192        | 0.12  | 150  | 0.3561          |
| 0.3546        | 0.16  | 200  | 0.3135          |
| 0.3119        | 0.2   | 250  | 0.2935          |
| 0.2926        | 0.24  | 300  | 0.2799          |
| 0.283         | 0.27  | 350  | 0.2711          |
| 0.2731        | 0.31  | 400  | 0.2629          |
| 0.2637        | 0.35  | 450  | 0.2583          |
| 0.2693        | 0.39  | 500  | 0.2518          |
| 0.2634        | 0.43  | 550  | 0.2478          |
| 0.2652        | 0.47  | 600  | 0.2453          |
| 0.2514        | 0.51  | 650  | 0.2429          |
| 0.2588        | 0.55  | 700  | 0.2394          |
| 0.2321        | 0.59  | 750  | 0.2381          |
| 0.2348        | 0.63  | 800  | 0.2357          |
| 0.2414        | 0.67  | 850  | 0.2355          |
| 0.2455        | 0.71  | 900  | 0.2337          |
| 0.2442        | 0.74  | 950  | 0.2331          |
| 0.2192        | 0.78  | 1000 | 0.2331          |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0