metadata
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-dpo-full
results: []
zephyr-7b-dpo-full
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.4893
- Rewards/chosen: -1.9379
- Rewards/rejected: -3.0213
- Rewards/accuracies: 0.7718
- Rewards/margins: 1.0835
- Logps/rejected: -563.9073
- Logps/chosen: -477.8896
- Logits/rejected: 0.6827
- Logits/chosen: -0.4606
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
---|---|---|---|---|---|---|---|---|---|---|---|
0.6338 | 0.1 | 100 | 0.6333 | -0.4184 | -0.6017 | 0.6865 | 0.1833 | -321.9407 | -325.9421 | -2.4857 | -2.5392 |
0.5643 | 0.21 | 200 | 0.5547 | -1.1977 | -1.8547 | 0.7480 | 0.6570 | -447.2422 | -403.8748 | 0.1190 | -0.4672 |
0.5066 | 0.31 | 300 | 0.5214 | -0.9561 | -1.7858 | 0.7778 | 0.8297 | -440.3582 | -379.7161 | -0.7390 | -1.4155 |
0.4941 | 0.42 | 400 | 0.5082 | -1.2581 | -2.1325 | 0.7599 | 0.8744 | -475.0238 | -409.9142 | 0.1688 | -0.7662 |
0.506 | 0.52 | 500 | 0.5090 | -1.1067 | -2.0712 | 0.7639 | 0.9645 | -468.8966 | -394.7739 | 1.3983 | 0.0857 |
0.4893 | 0.63 | 600 | 0.4953 | -1.4696 | -2.4963 | 0.7579 | 1.0267 | -511.4048 | -431.0652 | 0.9613 | -0.4181 |
0.4558 | 0.73 | 700 | 0.4937 | -1.8124 | -2.8894 | 0.7698 | 1.0770 | -550.7128 | -465.3409 | 0.6946 | -0.4445 |
0.4781 | 0.84 | 800 | 0.4898 | -1.9968 | -3.0983 | 0.7698 | 1.1015 | -571.6086 | -483.7863 | 0.7311 | -0.4503 |
0.495 | 0.94 | 900 | 0.4894 | -1.9365 | -3.0176 | 0.7698 | 1.0812 | -563.5378 | -477.7505 | 0.6757 | -0.4642 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.0