---
license: mit
base_model: microsoft/phi-1_5
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: phi-1_5_sft
  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-1_5_sft

This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the HuggingFaceH4/ultrachat_200k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2542

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 120
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3099        | 0.1   | 100  | 1.3398          |
| 1.3131        | 0.2   | 200  | 1.3159          |
| 1.3009        | 0.3   | 300  | 1.3046          |
| 1.2915        | 0.4   | 400  | 1.2967          |
| 1.2714        | 0.5   | 500  | 1.2906          |
| 1.2811        | 0.6   | 600  | 1.2854          |
| 1.2621        | 0.7   | 700  | 1.2807          |
| 1.2406        | 0.8   | 800  | 1.2767          |
| 1.2371        | 0.9   | 900  | 1.2731          |
| 1.2547        | 1.0   | 1000 | 1.2699          |
| 1.2085        | 1.1   | 1100 | 1.2693          |
| 1.2253        | 1.2   | 1200 | 1.2669          |
| 1.215         | 1.3   | 1300 | 1.2649          |
| 1.2103        | 1.4   | 1400 | 1.2630          |
| 1.2081        | 1.5   | 1500 | 1.2612          |
| 1.2033        | 1.6   | 1600 | 1.2597          |
| 1.2307        | 1.7   | 1700 | 1.2582          |
| 1.2038        | 1.8   | 1800 | 1.2568          |
| 1.2014        | 1.9   | 1900 | 1.2557          |
| 1.188         | 2.0   | 2000 | 1.2546          |
| 1.1473        | 2.1   | 2100 | 1.2563          |
| 1.1872        | 2.2   | 2200 | 1.2559          |
| 1.2086        | 2.3   | 2300 | 1.2553          |
| 1.1896        | 2.4   | 2400 | 1.2550          |
| 1.1733        | 2.5   | 2500 | 1.2548          |
| 1.1665        | 2.6   | 2600 | 1.2544          |
| 1.1499        | 2.7   | 2700 | 1.2543          |
| 1.1779        | 2.8   | 2800 | 1.2542          |
| 1.1746        | 2.9   | 2900 | 1.2542          |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0