---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0507HMA15HV2
  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. -->

# V0507HMA15HV2

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: -95.0498

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| -8.6532       | 0.09  | 10   | -10.3327        |
| -11.8451      | 0.18  | 20   | -14.2014        |
| -17.3537      | 0.27  | 30   | -22.7794        |
| -28.8388      | 0.36  | 40   | -38.5512        |
| -47.1885      | 0.45  | 50   | -59.6364        |
| -67.2573      | 0.54  | 60   | -76.6591        |
| -81.223       | 0.63  | 70   | -86.3414        |
| -87.9651      | 0.73  | 80   | -90.0475        |
| -91.3192      | 0.82  | 90   | -92.4350        |
| -92.7456      | 0.91  | 100  | -93.1825        |
| -93.4032      | 1.0   | 110  | -93.7378        |
| -93.8855      | 1.09  | 120  | -93.9331        |
| -94.0075      | 1.18  | 130  | -93.9987        |
| -94.001       | 1.27  | 140  | -94.3115        |
| -94.3566      | 1.36  | 150  | -94.4505        |
| -94.3346      | 1.45  | 160  | -94.2625        |
| -94.5793      | 1.54  | 170  | -94.3309        |
| -93.2701      | 1.63  | 180  | -93.4388        |
| -94.2829      | 1.72  | 190  | -93.8681        |
| -94.6778      | 1.81  | 200  | -94.7489        |
| -94.5762      | 1.9   | 210  | -94.7745        |
| -94.8427      | 1.99  | 220  | -94.8903        |
| -94.8653      | 2.08  | 230  | -94.8499        |
| -94.9237      | 2.18  | 240  | -94.9720        |
| -95.0027      | 2.27  | 250  | -94.9841        |
| -94.9404      | 2.36  | 260  | -94.8479        |
| -94.9594      | 2.45  | 270  | -95.0076        |
| -95.0772      | 2.54  | 280  | -95.0798        |
| -95.0775      | 2.63  | 290  | -95.0480        |
| -95.0528      | 2.72  | 300  | -95.0415        |
| -95.0652      | 2.81  | 310  | -95.0442        |
| -95.0738      | 2.9   | 320  | -95.0494        |
| -95.0694      | 2.99  | 330  | -95.0498        |


### Framework versions

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