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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: 0.0224
- Rewards/chosen: -1.9945
- Rewards/rejected: -3.2919
- Rewards/accuracies: 0.7148
- Rewards/margins: 1.2974
- Logps/rejected: -640.8138
- Logps/chosen: -503.0325
- Logits/rejected: 0.3215
- Logits/chosen: 0.2841
## 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: 1e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 4
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.111 | 0.21 | 100 | 0.1080 | -0.3300 | -0.6434 | 0.7148 | 0.3134 | -375.9606 | -336.5851 | 0.4520 | 0.3976 |
| 0.0697 | 0.42 | 200 | 0.0728 | -0.5844 | -1.2213 | 0.7422 | 0.6369 | -433.7567 | -362.0242 | 0.4101 | 0.3267 |
| 0.055 | 0.63 | 300 | 0.0610 | -0.7945 | -1.5421 | 0.7266 | 0.7476 | -465.8376 | -383.0369 | 0.2780 | 0.2451 |
| 0.0573 | 0.84 | 400 | 0.0566 | -0.8305 | -1.5952 | 0.7383 | 0.7647 | -471.1477 | -386.6394 | 0.2561 | 0.2348 |
| 0.0215 | 1.05 | 500 | 0.0327 | -1.6150 | -2.8668 | 0.7305 | 1.2517 | -598.3008 | -465.0880 | 0.2419 | 0.2221 |
| 0.0139 | 1.26 | 600 | 0.0260 | -1.8080 | -3.0895 | 0.7227 | 1.2815 | -620.5768 | -484.3871 | 0.2916 | 0.2601 |
| 0.0125 | 1.47 | 700 | 0.0247 | -1.9121 | -3.1886 | 0.7305 | 1.2765 | -630.4850 | -494.7950 | 0.2947 | 0.2614 |
| 0.0107 | 1.67 | 800 | 0.0226 | -1.9947 | -3.2951 | 0.7188 | 1.3004 | -641.1344 | -503.0576 | 0.3196 | 0.2841 |
| 0.0106 | 1.88 | 900 | 0.0224 | -1.9945 | -3.2919 | 0.7148 | 1.2974 | -640.8138 | -503.0325 | 0.3215 | 0.2841 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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