---
library_name: peft
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: phi2-mentalchat16k
  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-mentalchat16k

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7112

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8915        | 0.1496 | 100  | 0.8518          |
| 0.8464        | 0.2992 | 200  | 0.8102          |
| 0.7874        | 0.4488 | 300  | 0.7927          |
| 0.7999        | 0.5984 | 400  | 0.7814          |
| 0.7901        | 0.7479 | 500  | 0.7731          |
| 0.7801        | 0.8975 | 600  | 0.7647          |
| 0.7585        | 1.0471 | 700  | 0.7639          |
| 0.7592        | 1.1967 | 800  | 0.7576          |
| 0.7431        | 1.3463 | 900  | 0.7542          |
| 0.7555        | 1.4959 | 1000 | 0.7501          |
| 0.7354        | 1.6455 | 1100 | 0.7456          |
| 0.7281        | 1.7951 | 1200 | 0.7422          |
| 0.7312        | 1.9447 | 1300 | 0.7395          |
| 0.6984        | 2.0942 | 1400 | 0.7389          |
| 0.7037        | 2.2438 | 1500 | 0.7382          |
| 0.6913        | 2.3934 | 1600 | 0.7357          |
| 0.7229        | 2.5430 | 1700 | 0.7341          |
| 0.7095        | 2.6926 | 1800 | 0.7326          |
| 0.6994        | 2.8422 | 1900 | 0.7319          |
| 0.6995        | 2.9918 | 2000 | 0.7298          |
| 0.6887        | 3.1414 | 2100 | 0.7314          |
| 0.6712        | 3.2909 | 2200 | 0.7308          |
| 0.6867        | 3.4405 | 2300 | 0.7300          |
| 0.6817        | 3.5901 | 2400 | 0.7299          |
| 0.681         | 3.7397 | 2500 | 0.7296          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.4.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3