This model is a fine-tuned version of llama small config.json on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.0263 Num Input Tokens Seen: 0 Model description
--- library_name: transformers base_model: llama_small_config.json tags: - generated_from_trainer model-index: - name: convergent-llama-300M-muon-base15-addition_base15 results: [] --- # convergent-llama-300M-muon-base15-addition_base15 This model is a fine-tuned version of [llama_small_config.json](https://huggingface.co/llama_small_config.json) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0263 - Num Input Tokens Seen: 0 ## 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: 0.0003 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 16 - total_train_batch_size: 512 - total_eval_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 500 - training_steps: 10000 ### Training results ### Framework versions - Transformers 5.3.0 - Pytorch 2.10.0+cu128 - Datasets 4.7.0 - Tokenizers 0.22.2
This model is a fine-tuned version of llama small config.json on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.0263 Num Input Tokens Seen: 0 Model description
