metadata
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/phi-2
model-index:
- name: results
results: []
results
This model is a fine-tuned version of microsoft/phi-2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8902
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- 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
- lr_scheduler_warmup_steps: 150
- num_epochs: 0.5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7893 | 0.04 | 25 | 0.9209 |
| 0.7162 | 0.07 | 50 | 0.9266 |
| 0.9178 | 0.11 | 75 | 0.8747 |
| 0.7546 | 0.14 | 100 | 0.8973 |
| 0.8387 | 0.18 | 125 | 0.8814 |
| 0.7346 | 0.21 | 150 | 0.8926 |
| 0.8609 | 0.25 | 175 | 0.8971 |
| 0.7118 | 0.29 | 200 | 0.8833 |
| 0.8248 | 0.32 | 225 | 0.8747 |
| 0.6511 | 0.36 | 250 | 0.8852 |
| 0.9178 | 0.39 | 275 | 0.8744 |
| 0.6139 | 0.43 | 300 | 0.8885 |
| 0.8795 | 0.46 | 325 | 0.8802 |
| 0.5775 | 0.5 | 350 | 0.8902 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1
Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
Framework versions
- PEFT 0.6.2