---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0507HMA15HB2
  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. -->

# V0507HMA15HB2

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: -81.6054

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| -10.1232      | 0.09  | 10   | -11.7425        |
| -13.0448      | 0.18  | 20   | -15.0037        |
| -17.5347      | 0.27  | 30   | -21.6644        |
| -25.551       | 0.36  | 40   | -31.2337        |
| -35.3456      | 0.45  | 50   | -41.1929        |
| -44.7681      | 0.54  | 60   | -50.2314        |
| -53.1455      | 0.63  | 70   | -57.6267        |
| -59.6872      | 0.73  | 80   | -63.3874        |
| -65.1855      | 0.82  | 90   | -67.4235        |
| -67.6972      | 0.91  | 100  | -68.9758        |
| -70.4407      | 1.0   | 110  | -72.7099        |
| -73.0595      | 1.09  | 120  | -72.9839        |
| -72.4114      | 1.18  | 130  | -73.4895        |
| -73.3489      | 1.27  | 140  | -73.0341        |
| -68.9142      | 1.36  | 150  | -71.6919        |
| -75.8434      | 1.45  | 160  | -76.9335        |
| -77.7082      | 1.54  | 170  | -79.3035        |
| -79.5405      | 1.63  | 180  | -78.0217        |
| -73.5315      | 1.72  | 190  | -72.0316        |
| -72.5674      | 1.81  | 200  | -74.5039        |
| -76.8928      | 1.9   | 210  | -77.8919        |
| -78.6004      | 1.99  | 220  | -79.7306        |
| -79.779       | 2.08  | 230  | -78.9037        |
| -78.5156      | 2.18  | 240  | -78.2094        |
| -77.3853      | 2.27  | 250  | -74.1239        |
| -77.7728      | 2.36  | 260  | -79.7795        |
| -80.4204      | 2.45  | 270  | -81.1776        |
| -81.1502      | 2.54  | 280  | -81.5114        |
| -81.4538      | 2.63  | 290  | -81.3391        |
| -81.3301      | 2.72  | 300  | -81.3797        |
| -81.3074      | 2.81  | 310  | -81.5299        |
| -81.527       | 2.9   | 320  | -81.5893        |
| -81.5978      | 2.99  | 330  | -81.6054        |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1