metadata
license: mit
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
base_model: microsoft/phi-2
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: output_dir
results: []
output_dir
This model is a fine-tuned version of phi_2_instruction on the HuggingFaceH4/ultrafeedback_binarized dataset.
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-07
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.2.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 62.33 |
| AI2 Reasoning Challenge (25-Shot) | 63.05 |
| HellaSwag (10-Shot) | 76.36 |
| MMLU (5-Shot) | 58.46 |
| TruthfulQA (0-shot) | 45.35 |
| Winogrande (5-shot) | 74.03 |
| GSM8k (5-shot) | 56.71 |