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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-ultrabin-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-ultrabin-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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0345
- Rewards/chosen: -0.1240
- Rewards/rejected: -0.4158
- Rewards/accuracies: 0.7734
- Rewards/margins: 0.2918
- Logps/rejected: -304.2409
- Logps/chosen: -275.0308
- Logits/rejected: -2.4195
- Logits/chosen: -2.5003
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0497 | 0.1046 | 50 | 0.0471 | 0.0341 | -0.0639 | 0.6953 | 0.0980 | -269.0505 | -259.2180 | -2.5747 | -2.6118 |
| 0.0399 | 0.2092 | 100 | 0.0400 | -0.0674 | -0.3039 | 0.7656 | 0.2365 | -293.0492 | -269.3653 | -2.2263 | -2.2796 |
| 0.0384 | 0.3138 | 150 | 0.0368 | -0.1521 | -0.4051 | 0.7812 | 0.2530 | -303.1761 | -277.8396 | -2.4575 | -2.5017 |
| 0.0354 | 0.4184 | 200 | 0.0368 | -0.1608 | -0.4413 | 0.7812 | 0.2805 | -306.7949 | -278.7134 | -2.6355 | -2.6785 |
| 0.035 | 0.5230 | 250 | 0.0359 | -0.0276 | -0.3002 | 0.7812 | 0.2726 | -292.6817 | -265.3905 | -2.5364 | -2.5931 |
| 0.0336 | 0.6276 | 300 | 0.0351 | -0.1609 | -0.4489 | 0.7734 | 0.2880 | -307.5566 | -278.7195 | -2.3179 | -2.4060 |
| 0.0338 | 0.7322 | 350 | 0.0348 | -0.1145 | -0.3940 | 0.7695 | 0.2795 | -302.0604 | -274.0787 | -2.3603 | -2.4329 |
| 0.0352 | 0.8368 | 400 | 0.0345 | -0.1250 | -0.4112 | 0.7734 | 0.2863 | -303.7862 | -275.1277 | -2.4372 | -2.5111 |
| 0.0342 | 0.9414 | 450 | 0.0345 | -0.1240 | -0.4158 | 0.7734 | 0.2918 | -304.2409 | -275.0308 | -2.4195 | -2.5003 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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