File size: 5,447 Bytes
3b29619 c7d92f2 3b29619 c7d92f2 3b29619 c7d92f2 3b29619 c7d92f2 3b29619 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 |
---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
- AmberYifan/safetyQA_DPO
model-index:
- name: zephyr-7b-sft-safeDPO
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# zephyr-7b-sft-safeDPO
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized and the AmberYifan/safetyQA_DPO datasets.
It achieves the following results on the evaluation set:
- Loss: 0.5427
- Rewards/chosen: -2.2653
- Rewards/rejected: -2.9944
- Rewards/accuracies: 0.7197
- Rewards/margins: 0.7291
- Logps/rejected: -469.7640
- Logps/chosen: -389.2892
- Logits/rejected: -1.7787
- Logits/chosen: -1.7892
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6809 | 0.06 | 100 | 0.6816 | -0.0896 | -0.1145 | 0.6090 | 0.0249 | -181.7760 | -171.7131 | -2.5505 | -2.5392 |
| 0.6002 | 0.12 | 200 | 0.5906 | -1.4710 | -1.9163 | 0.6844 | 0.4453 | -361.9523 | -309.8549 | -2.3566 | -2.3656 |
| 0.591 | 0.17 | 300 | 0.5809 | -2.0305 | -2.5280 | 0.6924 | 0.4975 | -423.1273 | -365.8047 | -2.1933 | -2.2068 |
| 0.5437 | 0.23 | 400 | 0.5684 | -1.8038 | -2.3666 | 0.7032 | 0.5628 | -406.9888 | -343.1347 | -1.8974 | -1.9247 |
| 0.5415 | 0.29 | 500 | 0.5648 | -2.4230 | -3.0650 | 0.7066 | 0.6419 | -476.8223 | -405.0594 | -1.7952 | -1.8126 |
| 0.564 | 0.35 | 600 | 0.5578 | -2.3499 | -2.9909 | 0.7192 | 0.6409 | -469.4118 | -397.7481 | -1.8836 | -1.8847 |
| 0.5769 | 0.4 | 700 | 0.5598 | -2.2030 | -2.8326 | 0.7032 | 0.6296 | -453.5823 | -383.0532 | -1.7859 | -1.7719 |
| 0.5598 | 0.46 | 800 | 0.5586 | -2.2442 | -2.8471 | 0.7163 | 0.6029 | -455.0379 | -387.1816 | -1.7087 | -1.7061 |
| 0.5374 | 0.52 | 900 | 0.5555 | -2.1983 | -2.8363 | 0.7152 | 0.6379 | -453.9529 | -382.5883 | -1.6598 | -1.6767 |
| 0.5036 | 0.58 | 1000 | 0.5499 | -2.2315 | -2.9217 | 0.7209 | 0.6902 | -462.5011 | -385.9115 | -1.7160 | -1.7254 |
| 0.5281 | 0.63 | 1100 | 0.5489 | -2.2855 | -2.9604 | 0.7237 | 0.6749 | -466.3712 | -391.3100 | -1.7504 | -1.7563 |
| 0.5067 | 0.69 | 1200 | 0.5448 | -2.3024 | -3.0075 | 0.7243 | 0.7051 | -471.0760 | -393.0004 | -1.7967 | -1.8047 |
| 0.5095 | 0.75 | 1300 | 0.5451 | -2.2081 | -2.9003 | 0.7186 | 0.6922 | -460.3614 | -383.5680 | -1.8238 | -1.8248 |
| 0.5265 | 0.81 | 1400 | 0.5436 | -2.2844 | -2.9947 | 0.7215 | 0.7103 | -469.7991 | -391.1993 | -1.7998 | -1.8071 |
| 0.4844 | 0.86 | 1500 | 0.5433 | -2.2422 | -2.9533 | 0.7197 | 0.7112 | -465.6614 | -386.9761 | -1.7888 | -1.7993 |
| 0.5612 | 0.92 | 1600 | 0.5427 | -2.2671 | -2.9948 | 0.7209 | 0.7278 | -469.8113 | -389.4626 | -1.7766 | -1.7876 |
| 0.5017 | 0.98 | 1700 | 0.5426 | -2.2658 | -2.9947 | 0.7215 | 0.7289 | -469.7990 | -389.3405 | -1.7796 | -1.7904 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
|