metadata
library_name: transformers
license: other
base_model: microsoft/Phi-3.5-mini-instruct
tags:
- llama-factory
- freeze
- generated_from_trainer
model-index:
- name: microsoft/Phi-3.5-mini-instruct
results: []
my DC sever
我正在計畫微調64K指令模型，請幫助我進行計畫
Support me here if you're interested:
Ko-fi: https://ko-fi.com/ogodwin10
Phi-3.5-mini-instruct-24-9-29
This model is a fine-tuned version of microsoft/Phi-3.5-mini-instruct on the lmsys_chat dataset. It achieves the following results on the evaluation set:
- Loss: 1.3194
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: reduce_lr_on_plateau
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.428 | 0.0160 | 100 | 1.3194 |
| 1.2653 | 0.0320 | 200 | 1.3194 |
| 1.3084 | 0.0480 | 300 | 1.3194 |
| 1.3234 | 0.0641 | 400 | 1.3194 |
| 1.4091 | 0.0801 | 500 | 1.3194 |
| 1.2878 | 0.0961 | 600 | 1.3194 |
| 1.2933 | 0.1121 | 700 | 1.3194 |
| 1.3246 | 0.1281 | 800 | 1.3194 |
| 1.2911 | 0.1441 | 900 | 1.3194 |
| 1.4227 | 0.1602 | 1000 | 1.3194 |
Framework versions
- Transformers 4.45.0
- Pytorch 2.4.0+cu124
- Datasets 2.19.1
- Tokenizers 0.20.0