|
--- |
|
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-Extended-V3 |
|
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-MEDQA-Extended-V3 |
|
|
|
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: 0.6233 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 64 |
|
- 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 | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 0.7825 | 0.0882 | 200 | 0.6760 | |
|
| 0.6593 | 0.1764 | 400 | 0.6488 | |
|
| 0.6454 | 0.2646 | 600 | 0.6424 | |
|
| 0.6424 | 0.3528 | 800 | 0.6382 | |
|
| 0.6382 | 0.4410 | 1000 | 0.6358 | |
|
| 0.6342 | 0.5292 | 1200 | 0.6340 | |
|
| 0.6355 | 0.6174 | 1400 | 0.6327 | |
|
| 0.6355 | 0.7055 | 1600 | 0.6315 | |
|
| 0.6336 | 0.7937 | 1800 | 0.6307 | |
|
| 0.6321 | 0.8819 | 2000 | 0.6298 | |
|
| 0.6321 | 0.9701 | 2200 | 0.6291 | |
|
| 0.6298 | 1.0583 | 2400 | 0.6286 | |
|
| 0.6285 | 1.1465 | 2600 | 0.6280 | |
|
| 0.628 | 1.2347 | 2800 | 0.6275 | |
|
| 0.6282 | 1.3229 | 3000 | 0.6271 | |
|
| 0.6278 | 1.4111 | 3200 | 0.6267 | |
|
| 0.6257 | 1.4993 | 3400 | 0.6264 | |
|
| 0.6276 | 1.5875 | 3600 | 0.6260 | |
|
| 0.6253 | 1.6757 | 3800 | 0.6256 | |
|
| 0.6253 | 1.7639 | 4000 | 0.6253 | |
|
| 0.6242 | 1.8521 | 4200 | 0.6250 | |
|
| 0.6252 | 1.9402 | 4400 | 0.6247 | |
|
| 0.6239 | 2.0284 | 4600 | 0.6246 | |
|
| 0.6222 | 2.1166 | 4800 | 0.6244 | |
|
| 0.6226 | 2.2048 | 5000 | 0.6242 | |
|
| 0.6219 | 2.2930 | 5200 | 0.6241 | |
|
| 0.6227 | 2.3812 | 5400 | 0.6240 | |
|
| 0.6195 | 2.4694 | 5600 | 0.6239 | |
|
| 0.6219 | 2.5576 | 5800 | 0.6237 | |
|
| 0.6221 | 2.6458 | 6000 | 0.6236 | |
|
| 0.6238 | 2.7340 | 6200 | 0.6235 | |
|
| 0.621 | 2.8222 | 6400 | 0.6234 | |
|
| 0.621 | 2.9104 | 6600 | 0.6234 | |
|
| 0.6222 | 2.9986 | 6800 | 0.6233 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.12.0 |
|
- Transformers 4.43.3 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
