---
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