metadata
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi-3-mini-QLoRA
results: []
phi-3-mini-QLoRA
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2186
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: 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9004 | 0.6645 | 100 | 0.3627 |
| 0.2515 | 1.3289 | 200 | 0.2269 |
| 0.2229 | 1.9934 | 300 | 0.2209 |
| 0.2181 | 2.6578 | 400 | 0.2186 |
Framework versions
- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.2.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0