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---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
datasets:
- generator
model-index:
- name: cls_alldata_phi3_v1
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. -->
# cls_alldata_phi3_v1
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4956
## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7566 | 0.0559 | 20 | 0.7643 |
| 0.6863 | 0.1117 | 40 | 0.7089 |
| 0.6538 | 0.1676 | 60 | 0.6706 |
| 0.6261 | 0.2235 | 80 | 0.6499 |
| 0.6402 | 0.2793 | 100 | 0.6321 |
| 0.594 | 0.3352 | 120 | 0.6226 |
| 0.5956 | 0.3911 | 140 | 0.6121 |
| 0.5743 | 0.4469 | 160 | 0.6016 |
| 0.5494 | 0.5028 | 180 | 0.5903 |
| 0.5861 | 0.5587 | 200 | 0.5887 |
| 0.5431 | 0.6145 | 220 | 0.5801 |
| 0.5404 | 0.6704 | 240 | 0.5746 |
| 0.5401 | 0.7263 | 260 | 0.5695 |
| 0.5363 | 0.7821 | 280 | 0.5644 |
| 0.5534 | 0.8380 | 300 | 0.5608 |
| 0.5936 | 0.8939 | 320 | 0.5552 |
| 0.5139 | 0.9497 | 340 | 0.5496 |
| 0.5096 | 1.0056 | 360 | 0.5468 |
| 0.4891 | 1.0615 | 380 | 0.5468 |
| 0.4524 | 1.1173 | 400 | 0.5433 |
| 0.4568 | 1.1732 | 420 | 0.5397 |
| 0.4462 | 1.2291 | 440 | 0.5374 |
| 0.4605 | 1.2849 | 460 | 0.5337 |
| 0.4469 | 1.3408 | 480 | 0.5328 |
| 0.458 | 1.3966 | 500 | 0.5313 |
| 0.4378 | 1.4525 | 520 | 0.5250 |
| 0.4654 | 1.5084 | 540 | 0.5232 |
| 0.4563 | 1.5642 | 560 | 0.5200 |
| 0.4664 | 1.6201 | 580 | 0.5155 |
| 0.4308 | 1.6760 | 600 | 0.5128 |
| 0.443 | 1.7318 | 620 | 0.5082 |
| 0.4508 | 1.7877 | 640 | 0.5070 |
| 0.4511 | 1.8436 | 660 | 0.4999 |
| 0.4467 | 1.8994 | 680 | 0.4996 |
| 0.4723 | 1.9553 | 700 | 0.4956 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |