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---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- trl
- dpo
- alignment-handbook
- 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: 0.0087
- Rewards/chosen: -0.0010
- Rewards/rejected: -0.1538
- Rewards/accuracies: 0.7759
- Rewards/margins: 0.1527
- Logps/rejected: -261.8980
- Logps/chosen: -285.1917
- Logits/rejected: -2.3893
- Logits/chosen: -2.4834
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.012 | 0.1147 | 50 | 0.0113 | 0.0776 | -0.0073 | 0.6983 | 0.0849 | -247.2525 | -277.3343 | -2.5025 | -2.5786 |
| 0.0111 | 0.2294 | 100 | 0.0100 | 0.0400 | -0.0817 | 0.7112 | 0.1217 | -254.6882 | -281.0889 | -2.3452 | -2.4456 |
| 0.0104 | 0.3440 | 150 | 0.0098 | -0.0092 | -0.1421 | 0.7284 | 0.1329 | -260.7338 | -286.0115 | -2.4006 | -2.4971 |
| 0.0096 | 0.4587 | 200 | 0.0093 | 0.0230 | -0.1186 | 0.7888 | 0.1416 | -258.3851 | -282.7939 | -2.4206 | -2.5115 |
| 0.0093 | 0.5734 | 250 | 0.0089 | -0.0116 | -0.1682 | 0.7845 | 0.1565 | -263.3386 | -286.2548 | -2.3653 | -2.4591 |
| 0.0096 | 0.6881 | 300 | 0.0088 | -0.0083 | -0.1589 | 0.7845 | 0.1506 | -262.4115 | -285.9173 | -2.3891 | -2.4814 |
| 0.0096 | 0.8028 | 350 | 0.0087 | -0.0041 | -0.1596 | 0.7802 | 0.1555 | -262.4817 | -285.5014 | -2.3906 | -2.4846 |
| 0.0093 | 0.9174 | 400 | 0.0087 | -0.0010 | -0.1538 | 0.7759 | 0.1527 | -261.8980 | -285.1917 | -2.3893 | -2.4834 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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