---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0507HMA15HV4
  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. -->

# V0507HMA15HV4

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: -90.3589

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| -10.2471      | 0.09  | 10   | -11.5048        |
| -12.7013      | 0.18  | 20   | -14.6171        |
| -17.062       | 0.27  | 30   | -21.1957        |
| -25.2942      | 0.36  | 40   | -31.1893        |
| -35.8779      | 0.45  | 50   | -42.0890        |
| -45.8598      | 0.54  | 60   | -51.0205        |
| -54.2561      | 0.63  | 70   | -59.2111        |
| -62.3661      | 0.73  | 80   | -66.9216        |
| -69.4503      | 0.82  | 90   | -73.1015        |
| -75.6331      | 0.91  | 100  | -79.7275        |
| -80.4469      | 1.0   | 110  | -79.1007        |
| -82.9062      | 1.09  | 120  | -78.7341        |
| -79.1302      | 1.18  | 130  | -78.9765        |
| -80.7856      | 1.27  | 140  | -81.2231        |
| -82.8251      | 1.36  | 150  | -84.6507        |
| -85.8154      | 1.45  | 160  | -89.2273        |
| -87.8705      | 1.54  | 170  | -86.6222        |
| -87.8482      | 1.63  | 180  | -87.4917        |
| -89.9952      | 1.72  | 190  | -85.7639        |
| -88.213       | 1.81  | 200  | -88.9700        |
| -90.884       | 1.9   | 210  | -89.7730        |
| -90.422       | 1.99  | 220  | -89.8904        |
| -89.8791      | 2.08  | 230  | -90.1639        |
| -90.1325      | 2.18  | 240  | -90.1416        |
| -90.6013      | 2.27  | 250  | -89.7608        |
| -89.5485      | 2.36  | 260  | -89.8643        |
| -90.4119      | 2.45  | 270  | -90.7045        |
| -90.9852      | 2.54  | 280  | -90.5243        |
| -90.4856      | 2.63  | 290  | -90.2753        |
| -90.5832      | 2.72  | 300  | -90.5374        |
| -90.7252      | 2.81  | 310  | -90.4361        |
| -90.5843      | 2.9   | 320  | -90.3612        |
| -90.4331      | 2.99  | 330  | -90.3589        |


### Framework versions

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