metadata
license: mit
base_model: microsoft/Phi-3-mini-128k-instruct
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: phi-3-mini-128k-instruct-dpo-lr-5e-07
results: []
phi-3-mini-128k-instruct-dpo-lr-5e-07
This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6104
- Rewards/chosen: -1.0659
- Rewards/rejected: -1.4533
- Rewards/accuracies: 0.6976
- Rewards/margins: 0.3875
- Logps/rejected: -433.6641
- Logps/chosen: -403.0910
- Logits/rejected: 1.6821
- Logits/chosen: 1.6709
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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.62 | 0.8549 | 400 | 0.6104 | -1.0659 | -1.4533 | 0.6976 | 0.3875 | -433.6641 | -403.0910 | 1.6821 | 1.6709 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1