metadata
library_name: peft
license: other
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: lora
results: []
lora
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on the flock_task4_tranning dataset. It achieves the following results on the evaluation set:
- Loss: 1.1333
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1 | 0.0501 | 50 | 1.2970 |
| 1.0774 | 0.1002 | 100 | 1.2504 |
| 0.9563 | 0.1502 | 150 | 1.2521 |
| 1.0242 | 0.2003 | 200 | 1.2253 |
| 1.0038 | 0.2504 | 250 | 1.2113 |
| 0.9858 | 0.3005 | 300 | 1.1920 |
| 0.8694 | 0.3505 | 350 | 1.1918 |
| 0.9174 | 0.4006 | 400 | 1.1884 |
| 0.9653 | 0.4507 | 450 | 1.1870 |
| 0.9136 | 0.5008 | 500 | 1.1768 |
| 0.9014 | 0.5508 | 550 | 1.1673 |
| 0.9203 | 0.6009 | 600 | 1.1558 |
| 0.8902 | 0.6510 | 650 | 1.1679 |
| 0.9018 | 0.7011 | 700 | 1.1489 |
| 0.937 | 0.7511 | 750 | 1.1577 |
| 0.8984 | 0.8012 | 800 | 1.1463 |
| 0.8607 | 0.8513 | 850 | 1.1517 |
| 0.8698 | 0.9014 | 900 | 1.1436 |
| 0.9661 | 0.9514 | 950 | 1.1479 |
| 0.672 | 1.0010 | 1000 | 1.1459 |
| 0.8162 | 1.0511 | 1050 | 1.1374 |
| 0.8477 | 1.1012 | 1100 | 1.1434 |
| 0.9039 | 1.1512 | 1150 | 1.1394 |
| 0.8361 | 1.2013 | 1200 | 1.1434 |
| 0.8091 | 1.2514 | 1250 | 1.1391 |
| 0.7854 | 1.3015 | 1300 | 1.1392 |
| 0.7716 | 1.3515 | 1350 | 1.1403 |
| 0.8637 | 1.4016 | 1400 | 1.1337 |
| 0.8491 | 1.4517 | 1450 | 1.1392 |
| 0.9037 | 1.5018 | 1500 | 1.1325 |
| 0.8698 | 1.5518 | 1550 | 1.1371 |
| 0.7614 | 1.6019 | 1600 | 1.1332 |
| 0.7492 | 1.6520 | 1650 | 1.1350 |
| 0.8217 | 1.7021 | 1700 | 1.1321 |
| 0.8261 | 1.7521 | 1750 | 1.1323 |
| 0.8286 | 1.8022 | 1800 | 1.1325 |
| 0.8208 | 1.8523 | 1850 | 1.1335 |
| 0.7937 | 1.9024 | 1900 | 1.1338 |
| 0.837 | 1.9524 | 1950 | 1.1342 |
Framework versions
- PEFT 0.12.0
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0