---
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.3
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: mistral_7b_0-3_oh-dcft-v3.1-llama-3.1-70b
  results: []
---

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# mistral_7b_0-3_oh-dcft-v3.1-llama-3.1-70b

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the mlfoundations-dev/oh-dcft-v3.1-llama-3.1-70b dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3472

## 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-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- total_train_batch_size: 512
- total_eval_batch_size: 256
- 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_with_min_lr
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3209        | 1.0   | 473  | 0.3239          |
| 0.2363        | 2.0   | 946  | 0.3176          |
| 0.1634        | 3.0   | 1419 | 0.3472          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.4.0
- Datasets 3.0.2
- Tokenizers 0.20.3