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---
base_model: data/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- 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 [data/zephyr-7b-sft-full](https://huggingface.co/data/zephyr-7b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5257
- Rewards/chosen: -0.6523
- Rewards/rejected: -1.4719
- Rewards/accuracies: 0.7695
- Rewards/margins: 0.8195
- Logps/rejected: -411.0257
- Logps/chosen: -329.0598
- Logits/rejected: 0.9901
- Logits/chosen: 0.7049
## 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5992 | 0.2092 | 100 | 0.5956 | -0.2932 | -0.6564 | 0.7148 | 0.3632 | -329.4821 | -293.1491 | -2.2402 | -2.2843 |
| 0.57 | 0.4184 | 200 | 0.5591 | -0.3908 | -0.9608 | 0.7422 | 0.5700 | -359.9165 | -302.9073 | -1.6390 | -1.7197 |
| 0.5222 | 0.6276 | 300 | 0.5473 | -0.4814 | -1.1717 | 0.7461 | 0.6902 | -381.0072 | -311.9707 | -1.3133 | -1.4138 |
| 0.5332 | 0.8368 | 400 | 0.5284 | -0.6175 | -1.4117 | 0.7539 | 0.7941 | -405.0050 | -325.5808 | 0.5323 | 0.2839 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.1.0a0+32f93b1
- Datasets 2.19.1
- Tokenizers 0.19.1
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