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---
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: []
---
<!-- 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
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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5046
- Rewards/chosen: -1.1826
- Rewards/rejected: -2.0581
- Rewards/accuracies: 0.7246
- Rewards/margins: 0.8756
- Logps/rejected: -470.5493
- Logps/chosen: -395.9858
- Logits/rejected: 0.0457
- Logits/chosen: -0.4473
## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 10
- total_train_batch_size: 120
- total_eval_batch_size: 12
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5764 | 0.2 | 100 | 0.5829 | -0.3592 | -0.7613 | 0.6931 | 0.4020 | -340.8605 | -313.6503 | -2.4360 | -2.4791 |
| 0.5169 | 0.39 | 200 | 0.5312 | -0.8847 | -1.6204 | 0.7066 | 0.7356 | -426.7720 | -366.2012 | -0.8443 | -1.2010 |
| 0.5133 | 0.59 | 300 | 0.5159 | -1.1886 | -1.9604 | 0.7246 | 0.7718 | -460.7765 | -396.5906 | 0.0460 | -0.3853 |
| 0.4968 | 0.79 | 400 | 0.5058 | -1.2445 | -2.1063 | 0.7141 | 0.8618 | -475.3639 | -402.1766 | 0.2014 | -0.2552 |
| 0.4833 | 0.98 | 500 | 0.5045 | -1.1821 | -2.0581 | 0.7260 | 0.8760 | -470.5448 | -395.9374 | 0.0436 | -0.4496 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
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