--- license: llama3.1 base_model: meta-llama/Llama-3.1-8B-Instruct tags: - alignment-handbook - generated_from_trainer datasets: - JunxiongWang/sftdatasetv3 model-index: - name: Llama-Mamba2-3.1-8B-teacher-Llama-3.1-70B-Instruct-kl1.0-ce0.0 results: [] --- [Visualize in Weights & Biases](https://wandb.ai/junxiong12/huggingface/runs/ek2k9fvc) # Llama-Mamba2-3.1-8B-teacher-Llama-3.1-70B-Instruct-kl1.0-ce0.0 This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the JunxiongWang/sftdatasetv3 dataset. It achieves the following results on the evaluation set: - Loss: 268.4026 ## 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: 2e-05 - train_batch_size: 2 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.01 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:-----:|:---------------:| | 236.7 | 1.0000 | 51995 | 268.4026 | ### Framework versions - Transformers 4.43.1 - Pytorch 2.1.1+cu118 - Datasets 2.20.0 - Tokenizers 0.19.1