---
library_name: transformers
base_model: mistral-7b-base-sft-hh-harmless-4xh200-batch-64-20260418-015332
tags:
- alignment-handbook
- beta-dpo
- generated_from_trainer
datasets:
- Anthropic/hh-rlhf
model-index:
- name: mistral-7b-base-beta-dpo-hh-harmless-4xh200-batch-64-20260418-015332
  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. -->

# mistral-7b-base-beta-dpo-hh-harmless-4xh200-batch-64-20260418-015332

This model is a fine-tuned version of [mistral-7b-base-sft-hh-harmless-4xh200-batch-64-20260418-015332](https://huggingface.co/mistral-7b-base-sft-hh-harmless-4xh200-batch-64-20260418-015332) on the Anthropic/hh-rlhf dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2926
- Beta Dpo/beta: 0.1601
- Beta Dpo/loss Margin Mean: 39.2063
- Beta Dpo/beta Margin Mean: 8.1315
- Beta Dpo/beta Margin Std: 10.1723
- Beta Dpo/beta Margin Grad Mean: -0.3823
- Beta Dpo/beta Margin Grad Std: 0.1665
- Beta Dpo/gap Mean: 43.6826
- Beta Dpo/gap Std: 65.1157
- Beta Dpo/beta Used Raw: -0.1686
- Beta Dpo/beta Used: 0.1601
- Beta Dpo/mask Keep Frac: 1.0
- Logits/chosen: -2.7393
- Logits/rejected: -2.7541

## 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: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Beta Dpo/beta | Beta Dpo/loss Margin Mean | Beta Dpo/beta Margin Mean | Beta Dpo/beta Margin Std | Beta Dpo/beta Margin Grad Mean | Beta Dpo/beta Margin Grad Std | Beta Dpo/gap Mean | Beta Dpo/gap Std | Beta Dpo/beta Used Raw | Beta Dpo/beta Used | Beta Dpo/mask Keep Frac | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:-------------:|:-------------------------:|:-------------------------:|:------------------------:|:------------------------------:|:-----------------------------:|:-----------------:|:----------------:|:----------------------:|:------------------:|:-----------------------:|:-------------:|:---------------:|
| 0.9953        | 0.1512 | 100  | 0.6485          | 0.0613        | 9.1290                    | 0.7724                    | 1.1312                   | -0.4201                        | 0.1227                        | 11.2317           | 17.3662          | -0.0262                | 0.0613             | 1.0                     | -3.3065       | -3.3155         |
| 1.0952        | 0.3023 | 200  | 0.6746          | 0.0160        | 14.8251                   | 0.3434                    | 0.4801                   | -0.4659                        | 0.0456                        | 21.0985           | 27.0643          | -0.2764                | 0.0160             | 1.0                     | -3.2893       | -3.2944         |
| 0.957         | 0.4535 | 300  | 0.6778          | 0.0089        | 18.5486                   | 0.2473                    | 0.3133                   | -0.4818                        | 0.0249                        | 27.7148           | 34.2356          | -0.4500                | 0.0089             | 1.0                     | -3.1462       | -3.1521         |
| 1.3632        | 0.6047 | 400  | 0.7275          | 0.0294        | 21.1309                   | 0.9101                    | 1.1957                   | -0.4574                        | 0.0566                        | 28.7664           | 38.3785          | -0.3581                | 0.0294             | 1.0                     | -3.0744       | -3.0811         |
| 1.2415        | 0.7559 | 500  | 0.8583          | 0.0607        | 35.3740                   | 2.9334                    | 3.5974                   | -0.4353                        | 0.0818                        | 44.1570           | 58.8353          | -0.4270                | 0.0607             | 1.0                     | -2.7623       | -2.7786         |
| 2.3016        | 0.9070 | 600  | 1.2926          | 0.1601        | 39.2063                   | 8.1315                    | 10.1723                  | -0.3823                        | 0.1665                        | 43.6826           | 65.1157          | -0.1686                | 0.1601             | 1.0                     | -2.7393       | -2.7541         |


### Framework versions

- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4