---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/phi-1_5
model-index:
- name: phi-1_5-finetuned-qlora-cluster-gsm8k-v3-smallsubset
  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-finetuned-qlora-cluster-gsm8k-v3-smallsubset

This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4985

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.99  | 31   | 1.2173          |
| No log        | 1.98  | 62   | 1.1653          |
| No log        | 2.98  | 93   | 1.1535          |
| No log        | 4.0   | 125  | 1.1498          |
| No log        | 4.99  | 156  | 1.1562          |
| No log        | 5.98  | 187  | 1.1682          |
| 1.0347        | 6.98  | 218  | 1.1832          |
| 1.0347        | 8.0   | 250  | 1.1934          |
| 1.0347        | 8.99  | 281  | 1.2183          |
| 1.0347        | 9.98  | 312  | 1.2468          |
| 1.0347        | 10.98 | 343  | 1.2760          |
| 1.0347        | 12.0  | 375  | 1.3096          |
| 0.7791        | 12.99 | 406  | 1.3348          |
| 0.7791        | 13.98 | 437  | 1.3695          |
| 0.7791        | 14.98 | 468  | 1.3935          |
| 0.7791        | 16.0  | 500  | 1.4104          |
| 0.7791        | 16.99 | 531  | 1.4235          |
| 0.7791        | 17.98 | 562  | 1.4546          |
| 0.7791        | 18.98 | 593  | 1.4709          |
| 0.5995        | 20.0  | 625  | 1.4790          |
| 0.5995        | 20.99 | 656  | 1.4889          |
| 0.5995        | 21.98 | 687  | 1.4942          |
| 0.5995        | 22.98 | 718  | 1.4954          |
| 0.5995        | 24.0  | 750  | 1.4982          |
| 0.5995        | 24.8  | 775  | 1.4985          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.37.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1