| | --- |
| | 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 |
| | 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-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.7121 |
| |
|
| | ## 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 | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 1.94 | 0.0953 | 100 | 1.8918 | |
| | | 1.8113 | 0.1907 | 200 | 1.7877 | |
| | | 1.7578 | 0.2860 | 300 | 1.7701 | |
| | | 1.756 | 0.3813 | 400 | 1.7637 | |
| | | 1.7632 | 0.4766 | 500 | 1.7582 | |
| | | 1.7477 | 0.5720 | 600 | 1.7542 | |
| | | 1.7605 | 0.6673 | 700 | 1.7508 | |
| | | 1.7312 | 0.7626 | 800 | 1.7482 | |
| | | 1.7315 | 0.8580 | 900 | 1.7439 | |
| | | 1.7148 | 0.9533 | 1000 | 1.7414 | |
| | | 1.7263 | 1.0486 | 1100 | 1.7385 | |
| | | 1.7184 | 1.1439 | 1200 | 1.7361 | |
| | | 1.7187 | 1.2393 | 1300 | 1.7336 | |
| | | 1.7231 | 1.3346 | 1400 | 1.7313 | |
| | | 1.7433 | 1.4299 | 1500 | 1.7290 | |
| | | 1.6962 | 1.5253 | 1600 | 1.7268 | |
| | | 1.7136 | 1.6206 | 1700 | 1.7253 | |
| | | 1.6969 | 1.7159 | 1800 | 1.7236 | |
| | | 1.7028 | 1.8112 | 1900 | 1.7217 | |
| | | 1.7066 | 1.9066 | 2000 | 1.7200 | |
| | | 1.7123 | 2.0019 | 2100 | 1.7191 | |
| | | 1.7005 | 2.0972 | 2200 | 1.7178 | |
| | | 1.7052 | 2.1926 | 2300 | 1.7168 | |
| | | 1.6946 | 2.2879 | 2400 | 1.7160 | |
| | | 1.6728 | 2.3832 | 2500 | 1.7150 | |
| | | 1.7033 | 2.4786 | 2600 | 1.7144 | |
| | | 1.6893 | 2.5739 | 2700 | 1.7136 | |
| | | 1.7206 | 2.6692 | 2800 | 1.7129 | |
| | | 1.6747 | 2.7645 | 2900 | 1.7126 | |
| | | 1.6981 | 2.8599 | 3000 | 1.7123 | |
| | | 1.6928 | 2.9552 | 3100 | 1.7121 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.12.0 |
| | - Transformers 4.43.3 |
| | - Pytorch 2.3.1+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
