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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:
- 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: 0.4980
- Rewards/chosen: -2.1242
- Rewards/rejected: -3.0843
- Rewards/accuracies: 0.7380
- Rewards/margins: 0.9601
- Logps/rejected: -497.6194
- Logps/chosen: -397.4371
- Logits/rejected: -0.2690
- Logits/chosen: -0.8689
## 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: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 8
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5294 | 0.2617 | 500 | 0.5470 | -1.7358 | -2.3925 | 0.6980 | 0.6567 | -428.4361 | -358.6011 | -0.4724 | -0.8639 |
| 0.5232 | 0.5234 | 1000 | 0.5099 | -1.9184 | -2.7566 | 0.7160 | 0.8382 | -464.8497 | -376.8646 | -0.0573 | -0.6162 |
| 0.4707 | 0.7851 | 1500 | 0.5000 | -2.1875 | -3.1436 | 0.7320 | 0.9561 | -503.5489 | -403.7713 | -0.0548 | -0.6702 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.1.2
- Datasets 2.19.0
- Tokenizers 0.19.1
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