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---
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:
- Anthropic/hh-rlhf
model-index:
- name: zephyr-7b-dpo-full-hh
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-hh
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 Anthropic/hh-rlhf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5341
- Rewards/chosen: -2.5112
- Rewards/rejected: -3.3276
- Rewards/accuracies: 0.7295
- Rewards/margins: 0.8164
- Logps/rejected: -485.8198
- Logps/chosen: -398.0228
- Logits/rejected: 2.4839
- Logits/chosen: 1.8909
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6755 | 0.0796 | 100 | 0.6758 | -0.1176 | -0.1618 | 0.5830 | 0.0442 | -169.2391 | -158.6626 | -2.4575 | -2.4733 |
| 0.5965 | 0.1592 | 200 | 0.5934 | -1.0644 | -1.4934 | 0.6772 | 0.4290 | -302.3988 | -253.3484 | -0.2911 | -0.5108 |
| 0.5621 | 0.2388 | 300 | 0.5712 | -1.3390 | -1.8901 | 0.6875 | 0.5511 | -342.0688 | -280.8055 | 0.3164 | -0.1607 |
| 0.551 | 0.3183 | 400 | 0.5651 | -1.2110 | -1.8230 | 0.7192 | 0.6120 | -335.3575 | -268.0063 | -0.2086 | -0.6012 |
| 0.5696 | 0.3979 | 500 | 0.5572 | -1.8231 | -2.3956 | 0.7229 | 0.5725 | -392.6161 | -329.2127 | 0.5151 | 0.0872 |
| 0.5504 | 0.4775 | 600 | 0.5508 | -1.9233 | -2.7091 | 0.7201 | 0.7858 | -423.9663 | -339.2298 | 1.2370 | 0.4867 |
| 0.5387 | 0.5571 | 700 | 0.5417 | -2.3329 | -3.1152 | 0.7211 | 0.7823 | -464.5798 | -380.1928 | 1.9107 | 1.1807 |
| 0.5119 | 0.6367 | 800 | 0.5416 | -2.6721 | -3.5027 | 0.7276 | 0.8306 | -503.3281 | -414.1180 | 3.4443 | 2.7209 |
| 0.564 | 0.7163 | 900 | 0.5385 | -2.6361 | -3.3606 | 0.7183 | 0.7245 | -489.1202 | -410.5185 | 2.5529 | 1.9952 |
| 0.5201 | 0.7959 | 1000 | 0.5347 | -2.5021 | -3.2845 | 0.7229 | 0.7824 | -481.5121 | -397.1160 | 2.4306 | 1.8888 |
| 0.5341 | 0.8754 | 1100 | 0.5346 | -2.4898 | -3.2841 | 0.7295 | 0.7943 | -481.4664 | -395.8830 | 2.3851 | 1.8147 |
| 0.5394 | 0.9550 | 1200 | 0.5341 | -2.5107 | -3.3276 | 0.7295 | 0.8168 | -485.8161 | -397.9764 | 2.4847 | 1.8912 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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