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---
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 |