transformers tensorboard safetensors mistral text-generation alignment-handbook generated_from_trainer trl dpo conversational dataset:HuggingFaceH4/ultrafeedback_binarized base_model:alignment-handbook/zephyr-7b-sft-full license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-dpo-full
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# zephyr-7b-dpo-full

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 HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5026
- Rewards/chosen: -1.0472
- Rewards/rejected: -1.9901
- Rewards/accuracies: 0.7619
- Rewards/margins: 0.9430
- Logps/rejected: -460.7913
- Logps/chosen: -388.8264
- Logits/rejected: 1.7625
- Logits/chosen: 1.0392

## 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: 615
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5736        | 0.21  | 100  | 0.5842          | -0.3837        | -0.8468          | 0.7242             | 0.4632          | -346.4596      | -322.4754    | -2.3510         | -2.4330       |
| 0.5116        | 0.42  | 200  | 0.5308          | -0.9042        | -1.7331          | 0.7520             | 0.8289          | -435.0859      | -374.5288    | 0.5012          | 0.0459        |
| 0.5027        | 0.63  | 300  | 0.5084          | -0.8877        | -1.7467          | 0.7639             | 0.8590          | -436.4478      | -372.8834    | 1.8224          | 1.1385        |
| 0.4823        | 0.84  | 400  | 0.5037          | -1.1953        | -2.1521          | 0.7619             | 0.9568          | -476.9852      | -403.6375    | 1.9978          | 1.3075        |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
