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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-prometheus-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-prometheus-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: 0.0240
- Rewards/chosen: -0.1305
- Rewards/rejected: -0.3804
- Rewards/accuracies: 0.7328
- Rewards/margins: 0.2499
- Logps/rejected: -286.3204
- Logps/chosen: -273.0143
- Logits/rejected: -2.4857
- Logits/chosen: -2.5477
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0371 | 0.1143 | 50 | 0.0330 | 0.0162 | -0.0844 | 0.6638 | 0.1006 | -256.7177 | -258.3393 | -2.5728 | -2.6169 |
| 0.0326 | 0.2286 | 100 | 0.0284 | -0.1604 | -0.3762 | 0.7069 | 0.2158 | -285.9020 | -276.0061 | -2.2908 | -2.3469 |
| 0.0276 | 0.3429 | 150 | 0.0261 | -0.1426 | -0.3607 | 0.7198 | 0.2181 | -284.3463 | -274.2200 | -2.3538 | -2.3992 |
| 0.0257 | 0.4571 | 200 | 0.0255 | -0.1250 | -0.3457 | 0.7371 | 0.2206 | -282.8442 | -272.4646 | -2.4669 | -2.5054 |
| 0.0259 | 0.5714 | 250 | 0.0249 | -0.1421 | -0.3761 | 0.7457 | 0.2340 | -285.8867 | -274.1743 | -2.5651 | -2.6093 |
| 0.0244 | 0.6857 | 300 | 0.0244 | -0.1115 | -0.3601 | 0.7328 | 0.2486 | -284.2852 | -271.1066 | -2.4931 | -2.5556 |
| 0.0232 | 0.8 | 350 | 0.0241 | -0.1203 | -0.3689 | 0.7328 | 0.2486 | -285.1674 | -271.9947 | -2.4940 | -2.5542 |
| 0.0253 | 0.9143 | 400 | 0.0240 | -0.1305 | -0.3804 | 0.7328 | 0.2499 | -286.3204 | -273.0143 | -2.4857 | -2.5477 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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