peft safetensors generated_from_trainer base_model:microsoft/phi-2 license:other region:us
---
license: other
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: phi2-ft-no_robots
  results: []
library_name: peft
---

<!-- 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-ft-no_robots

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: 2.0917

![logo](https://huggingface.co/mrm8488/phi2-ft-no_robots-adapter/resolve/main/logo.jpg)

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2.5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 66
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2187        | 0.15  | 20   | 2.1602          |
| 2.1689        | 0.29  | 40   | 2.1049          |
| 2.1977        | 0.44  | 60   | 2.0958          |
| 2.1587        | 0.59  | 80   | 2.0910          |
| 2.0382        | 0.74  | 100  | 2.0920          |
| 2.1622        | 0.88  | 120  | 2.0917          |


### Framework versions

- PEFT 0.4.0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
