--- library_name: transformers license: apache-2.0 base_model: mistralai/Mistral-7B-v0.1 tags: - llama-factory - full - generated_from_trainer model-index: - name: orca-agentinstruct-1M-v1-cleaned_mistral results: [] --- # orca-agentinstruct-1M-v1-cleaned_mistral This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the mlabonne/orca-agentinstruct-1M-v1-cleaned dataset. It achieves the following results on the evaluation set: - Loss: 0.4467 ## 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: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 32 - gradient_accumulation_steps: 2 - total_train_batch_size: 512 - total_eval_batch_size: 256 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant - lr_scheduler_warmup_ratio: 0.1 - lr_scheduler_warmup_steps: 1738 - num_epochs: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.417 | 0.9995 | 1035 | 0.4187 | | 0.3265 | 2.0 | 2071 | 0.4137 | | 0.2217 | 2.9986 | 3105 | 0.4467 | ### Framework versions - Transformers 4.45.2 - Pytorch 2.3.0 - Datasets 2.21.0 - Tokenizers 0.20.3