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-LoRA-MEDQA-V3
results: []
phi-3-mini-LoRA-MEDQA-V3
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: 0.6086
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
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6898 | 0.3633 | 100 | 0.6195 |
| 0.6113 | 0.7266 | 200 | 0.6134 |
| 0.6095 | 1.0899 | 300 | 0.6110 |
| 0.6034 | 1.4532 | 400 | 0.6103 |
| 0.6037 | 1.8165 | 500 | 0.6093 |
| 0.6043 | 2.1798 | 600 | 0.6089 |
| 0.5986 | 2.5431 | 700 | 0.6089 |
| 0.5993 | 2.9064 | 800 | 0.6086 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1