---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: sambar-7b-dpo-lora
  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. -->

# sambar-7b-dpo-lora

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5747
- Rewards/chosen: -0.0141
- Rewards/rejected: -0.4147
- Rewards/accuracies: 0.7060
- Rewards/margins: 0.4006
- Logps/rejected: -221.3069
- Logps/chosen: -263.0773
- Logits/rejected: -2.1478
- Logits/chosen: -2.2594

## 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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6213        | 1.0   | 242  | 0.6182          | 0.0426         | -0.1569          | 0.6860             | 0.1995          | -218.7293      | -262.5110    | -2.1605         | -2.2727       |
| 0.5903        | 2.0   | 484  | 0.5826          | 0.0046         | -0.3500          | 0.6940             | 0.3546          | -220.6603      | -262.8906    | -2.1517         | -2.2634       |
| 0.5743        | 3.0   | 726  | 0.5747          | -0.0141        | -0.4147          | 0.7060             | 0.4006          | -221.3069      | -263.0773    | -2.1478         | -2.2594       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1