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---
tags:
- trl
- dpo
- generated_from_trainer
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 was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6931
- Rewards/chosen: -2.1301
- Rewards/rejected: -2.1301
- Rewards/accuracies: 0.0
- Rewards/margins: 0.0
- Logps/rejected: -159.8372
- Logps/chosen: -159.8372
- Logits/rejected: -3.1995
- Logits/chosen: -3.1995
## 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: 2e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.3114 | 0.29 | 100 | 0.6931 | -2.8588 | -2.8588 | 0.0 | 0.0 | -161.2947 | -161.2947 | -3.2262 | -3.2262 |
| 0.2741 | 0.57 | 200 | 0.6931 | -2.6760 | -2.6760 | 0.0 | 0.0 | -160.9289 | -160.9289 | -3.2033 | -3.2033 |
| 0.2695 | 0.86 | 300 | 0.6931 | -2.1301 | -2.1301 | 0.0 | 0.0 | -159.8372 | -159.8372 | -3.1995 | -3.1995 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.2
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