peft tensorboard safetensors trl sft generated_from_trainer base_model:microsoft/phi-2 base_model:adapter:microsoft/phi-2 license:mit region:us
---
base_model: microsoft/phi-2
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: output_dir
  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. -->

# output_dir

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the SAMSUM (summarization) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8001

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8411        | 0.4   | 368  | 1.8439          |
| 1.6179        | 0.8   | 736  | 1.8187          |
| 1.5641        | 1.2   | 1104 | 1.8084          |
| 2.2357        | 1.6   | 1472 | 1.8017          |
| 1.388         | 2.0   | 1840 | 1.8001          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2