metadata
license: mit
library_name: peft
tags:
- trl
- orpo
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: orpo-phi3
results: []
orpo-phi3
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2224
- Rewards/chosen: -0.1152
- Rewards/rejected: -0.1838
- Rewards/accuracies: 1.0
- Rewards/margins: 0.0685
- Logps/rejected: -1.8375
- Logps/chosen: -1.1521
- Logits/rejected: -1.5266
- Logits/chosen: -0.4575
- Nll Loss: 1.1880
- Log Odds Ratio: -0.3436
- Log Odds Chosen: 0.8917
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: 8e-06
- train_batch_size: 2
- eval_batch_size: 2
- 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: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4.0204 | 0.24 | 3 | 1.2224 | -0.1152 | -0.1838 | 1.0 | 0.0685 | -1.8375 | -1.1521 | -1.5266 | -0.4575 | 1.1880 | -0.3436 | 0.8917 |
| 2.2028 | 0.48 | 6 | 1.2224 | -0.1152 | -0.1838 | 1.0 | 0.0685 | -1.8375 | -1.1521 | -1.5266 | -0.4575 | 1.1880 | -0.3436 | 0.8917 |
| 4.7852 | 0.72 | 9 | 1.2224 | -0.1152 | -0.1838 | 1.0 | 0.0685 | -1.8375 | -1.1521 | -1.5266 | -0.4575 | 1.1880 | -0.3436 | 0.8917 |
| 3.1295 | 0.96 | 12 | 1.2224 | -0.1152 | -0.1838 | 1.0 | 0.0685 | -1.8375 | -1.1521 | -1.5266 | -0.4575 | 1.1880 | -0.3436 | 0.8917 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1