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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: 0.5061
- Rewards/chosen: -1.0205
- Rewards/rejected: -1.9944
- Rewards/accuracies: 0.7812
- Rewards/margins: 0.9740
- Logps/rejected: -462.1064
- Logps/chosen: -364.6778
- Logits/rejected: 2.4089
- Logits/chosen: 1.6213
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5644 | 0.2092 | 100 | 0.5695 | -0.6773 | -1.2063 | 0.7188 | 0.5290 | -383.2874 | -330.3586 | -0.4241 | -0.6326 |
| 0.5445 | 0.4184 | 200 | 0.5354 | -0.6109 | -1.3936 | 0.7695 | 0.7827 | -402.0177 | -323.7153 | 0.9697 | 0.1924 |
| 0.4909 | 0.6276 | 300 | 0.5138 | -0.9252 | -1.8338 | 0.7578 | 0.9086 | -446.0438 | -355.1510 | 2.1667 | 1.4140 |
| 0.5036 | 0.8368 | 400 | 0.5066 | -0.9998 | -1.9548 | 0.7812 | 0.9549 | -458.1404 | -362.6149 | 2.3428 | 1.5651 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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