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---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full-gpt_consistent-reward-scale-1-rpo
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-gpt_consistent-reward-scale-1-rpo
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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0327
- Rewards/chosen: -0.1258
- Rewards/rejected: -0.4253
- Rewards/accuracies: 0.7543
- Rewards/margins: 0.2995
- Logps/rejected: -289.0509
- Logps/chosen: -297.6692
- Logits/rejected: -1.4762
- Logits/chosen: -1.6863
## 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: 55
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0487 | 0.1147 | 50 | 0.0455 | 0.0300 | -0.0845 | 0.7026 | 0.1145 | -254.9693 | -282.0912 | -2.4928 | -2.5717 |
| 0.0408 | 0.2294 | 100 | 0.0391 | -0.1071 | -0.3089 | 0.6897 | 0.2018 | -277.4089 | -295.8004 | -1.7416 | -1.8404 |
| 0.0379 | 0.3440 | 150 | 0.0365 | -0.1406 | -0.4136 | 0.7155 | 0.2730 | -287.8874 | -299.1519 | -1.6357 | -1.7904 |
| 0.0365 | 0.4587 | 200 | 0.0350 | -0.0650 | -0.3264 | 0.7543 | 0.2614 | -279.1631 | -291.5866 | -1.7552 | -1.9178 |
| 0.0346 | 0.5734 | 250 | 0.0337 | -0.1319 | -0.4539 | 0.7543 | 0.3220 | -291.9156 | -298.2828 | -1.4871 | -1.7192 |
| 0.036 | 0.6881 | 300 | 0.0331 | -0.1336 | -0.4291 | 0.75 | 0.2955 | -289.4286 | -298.4504 | -1.4842 | -1.6835 |
| 0.0359 | 0.8028 | 350 | 0.0327 | -0.1378 | -0.4472 | 0.7586 | 0.3094 | -291.2399 | -298.8666 | -1.4658 | -1.6786 |
| 0.0351 | 0.9174 | 400 | 0.0327 | -0.1258 | -0.4253 | 0.7543 | 0.2995 | -289.0509 | -297.6692 | -1.4762 | -1.6863 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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