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---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: phi-3-4k-instruct-domain-sft-1
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-3-4k-instruct-domain-sft-1
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9328
## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 128
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8958 | 0.1445 | 10 | 1.0716 |
| 1.7839 | 0.2890 | 20 | 1.0458 |
| 1.7146 | 0.4335 | 30 | 1.0222 |
| 1.6457 | 0.5780 | 40 | 1.0029 |
| 1.591 | 0.7225 | 50 | 0.9872 |
| 1.552 | 0.8670 | 60 | 0.9740 |
| 1.5115 | 1.0115 | 70 | 0.9631 |
| 1.4681 | 1.1560 | 80 | 0.9541 |
| 1.4469 | 1.3005 | 90 | 0.9468 |
| 1.419 | 1.4450 | 100 | 0.9412 |
| 1.4033 | 1.5895 | 110 | 0.9371 |
| 1.3928 | 1.7340 | 120 | 0.9343 |
| 1.3887 | 1.8785 | 130 | 0.9328 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1