---
library_name: transformers
base_model: lamm-mit/mistral-7B-v0.3-Instruct-CPT_SFT
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- lamm-mit/orpo-dpo-mix-40k
- lamm-mit/bio-inspired-DPO
- lamm-mit/spider-silk-DPO
model-index:
- name: mistral-7B-v0.3-Instruct-CPT_SFT-DPO
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mistral-7B-v0.3-Instruct-CPT_SFT-DPO

This model is a fine-tuned version of [lamm-mit/mistral-7B-v0.3-Instruct-CPT_SFT](https://huggingface.co/lamm-mit/mistral-7B-v0.3-Instruct-CPT_SFT) on the lamm-mit/orpo-dpo-mix-40k, the lamm-mit/bio-inspired-DPO and the lamm-mit/spider-silk-DPO datasets.

## 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: 4
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 8
- 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



### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1