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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-gamma-2
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-gamma-2
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: 0.1135
- Rewards/chosen: -0.4357
- Rewards/rejected: -0.9844
- Rewards/accuracies: 0.75
- Rewards/margins: 0.5488
- Logps/rejected: -344.9655
- Logps/chosen: -328.6565
- Logits/rejected: -1.1351
- Logits/chosen: -1.6080
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.1732 | 0.1147 | 50 | 0.1640 | 0.0148 | -0.1111 | 0.7069 | 0.1258 | -257.6288 | -283.6147 | -2.4924 | -2.5722 |
| 0.1403 | 0.2294 | 100 | 0.1362 | -0.1370 | -0.4667 | 0.6940 | 0.3297 | -293.1888 | -298.7873 | -1.8344 | -2.0560 |
| 0.1324 | 0.3440 | 150 | 0.1286 | -0.4769 | -0.9509 | 0.7371 | 0.4740 | -341.6123 | -332.7828 | -1.2887 | -1.6554 |
| 0.1249 | 0.4587 | 200 | 0.1217 | -0.2893 | -0.7611 | 0.7241 | 0.4719 | -322.6352 | -314.0176 | -1.4798 | -1.8578 |
| 0.1189 | 0.5734 | 250 | 0.1175 | -0.4263 | -0.9754 | 0.7629 | 0.5491 | -344.0638 | -327.7221 | -1.2227 | -1.6727 |
| 0.1252 | 0.6881 | 300 | 0.1154 | -0.4298 | -0.9852 | 0.7543 | 0.5554 | -345.0454 | -328.0691 | -1.1891 | -1.6634 |
| 0.1226 | 0.8028 | 350 | 0.1137 | -0.4793 | -1.0328 | 0.7543 | 0.5535 | -349.7979 | -333.0171 | -1.0590 | -1.5759 |
| 0.1206 | 0.9174 | 400 | 0.1135 | -0.4357 | -0.9844 | 0.75 | 0.5488 | -344.9655 | -328.6565 | -1.1351 | -1.6080 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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