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---
base_model: microsoft/Phi-3-mini-128k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi-3-mini-LoRA
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-mini-LoRA
This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co./microsoft/Phi-3-mini-128k-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3813
- eval_runtime: 140.2175
- eval_samples_per_second: 15.74
- eval_steps_per_second: 7.873
- epoch: 0.16
- step: 400
## 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: 1
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Framework versions
- PEFT 0.8.2
- Transformers 4.38.0
- Pytorch 2.2.1
- Datasets 2.17.0
- Tokenizers 0.15.2 |