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---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- trl
- dpo
- alignment-handbook
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full-gpt_consistent-reward-scale-1-rpo
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-dpo-full-gpt_consistent-reward-scale-1-rpo
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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1126
- Rewards/chosen: -0.4018
- Rewards/rejected: -0.9642
- Rewards/accuracies: 0.75
- Rewards/margins: 0.5623
- Logps/rejected: -342.9399
- Logps/chosen: -325.2745
- Logits/rejected: 0.1904
- Logits/chosen: -0.6159
## 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: 55
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.1732 | 0.1147 | 50 | 0.1640 | 0.0140 | -0.1117 | 0.7069 | 0.1256 | -257.6913 | -283.6945 | -2.4927 | -2.5723 |
| 0.1412 | 0.2294 | 100 | 0.1392 | -0.5601 | -0.9388 | 0.7198 | 0.3787 | -340.4027 | -341.0970 | -0.8338 | -1.1029 |
| 0.1327 | 0.3440 | 150 | 0.1257 | -0.3660 | -0.8686 | 0.7241 | 0.5025 | -333.3776 | -321.6920 | -0.4213 | -0.9346 |
| 0.1242 | 0.4587 | 200 | 0.1193 | -0.3424 | -0.8506 | 0.7457 | 0.5082 | -331.5807 | -319.3252 | -0.1498 | -0.9084 |
| 0.118 | 0.5734 | 250 | 0.1167 | -0.3734 | -0.9685 | 0.7543 | 0.5950 | -343.3683 | -322.4342 | -0.0251 | -0.8147 |
| 0.1236 | 0.6881 | 300 | 0.1145 | -0.4780 | -1.0449 | 0.7629 | 0.5669 | -351.0162 | -332.8936 | 0.2891 | -0.5285 |
| 0.122 | 0.8028 | 350 | 0.1127 | -0.4577 | -1.0376 | 0.7672 | 0.5799 | -350.2830 | -330.8570 | 0.3397 | -0.4806 |
| 0.12 | 0.9174 | 400 | 0.1126 | -0.4018 | -0.9642 | 0.75 | 0.5623 | -342.9399 | -325.2745 | 0.1904 | -0.6159 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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