metadata
base_model: alignment-handbook/zephyr-7b-sft-full
datasets:
- HuggingFaceH4/ultrafeedback_binarized
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-lora-r16-20k
results: []
zephyr-7b-dpo-lora-r16-20k
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: 0.5302
- Rewards/chosen: -0.7891
- Rewards/rejected: -1.4667
- Rewards/accuracies: 0.7183
- Rewards/margins: 0.6776
- Logps/rejected: -394.6997
- Logps/chosen: -362.1445
- Logits/rejected: -2.5080
- Logits/chosen: -2.5508
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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6899 | 0.08 | 100 | 0.6897 | 0.0098 | 0.0028 | 0.6667 | 0.0070 | -247.7543 | -282.2605 | -2.8468 | -2.8890 |
| 0.6532 | 0.16 | 200 | 0.6569 | -0.0128 | -0.0950 | 0.6885 | 0.0822 | -257.5306 | -284.5143 | -2.8386 | -2.8782 |
| 0.6372 | 0.24 | 300 | 0.6181 | -0.2381 | -0.4406 | 0.6825 | 0.2026 | -292.0921 | -307.0444 | -2.8033 | -2.8402 |
| 0.5699 | 0.32 | 400 | 0.6034 | -0.2658 | -0.5383 | 0.6964 | 0.2725 | -301.8563 | -309.8138 | -2.7952 | -2.8319 |
| 0.5622 | 0.4 | 500 | 0.5688 | -0.5565 | -0.9794 | 0.7143 | 0.4229 | -345.9727 | -338.8872 | -2.6913 | -2.7320 |
| 0.5826 | 0.48 | 600 | 0.5457 | -0.5456 | -1.1188 | 0.7242 | 0.5732 | -359.9116 | -337.7992 | -2.6523 | -2.6907 |
| 0.5313 | 0.56 | 700 | 0.5387 | -0.7142 | -1.3304 | 0.7242 | 0.6162 | -381.0734 | -354.6571 | -2.6173 | -2.6586 |
| 0.5332 | 0.64 | 800 | 0.5386 | -0.7256 | -1.3351 | 0.7183 | 0.6096 | -381.5442 | -355.7965 | -2.5760 | -2.6167 |
| 0.5334 | 0.72 | 900 | 0.5368 | -0.7061 | -1.3229 | 0.7163 | 0.6168 | -380.3204 | -353.8529 | -2.5574 | -2.5999 |
| 0.5837 | 0.8 | 1000 | 0.5302 | -0.7953 | -1.4787 | 0.7163 | 0.6834 | -395.8991 | -362.7657 | -2.5273 | -2.5706 |
| 0.5144 | 0.88 | 1100 | 0.5327 | -0.7410 | -1.4021 | 0.7123 | 0.6611 | -388.2353 | -357.3381 | -2.5162 | -2.5586 |
| 0.5196 | 0.96 | 1200 | 0.5301 | -0.7870 | -1.4645 | 0.7202 | 0.6775 | -394.4780 | -361.9388 | -2.5045 | -2.5477 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1