--- library_name: transformers license: llama3.2 base_model: meta-llama/Llama-3.2-1B-Instruct tags: - alignment-handbook - trl - sft - generated_from_trainer - trl - sft - alignment-handbook - generated_from_trainer datasets: - barc0/transduction_heavy_100k_jsonl - barc0/transduction_heavy_suggestfunction_100k_jsonl model-index: - name: heavy-200k-barc-llama3.2-1b-ins-fft-transduction_lr1e-5_epoch3 results: [] --- # heavy-200k-barc-llama3.2-1b-ins-fft-transduction_lr1e-5_epoch3 This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on the barc0/transduction_heavy_100k_jsonl and the barc0/transduction_heavy_suggestfunction_100k_jsonl datasets. It achieves the following results on the evaluation set: - Loss: 0.0407 ## 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: 1e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - total_train_batch_size: 64 - total_eval_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.0609 | 1.0 | 2956 | 0.0527 | | 0.042 | 2.0 | 5912 | 0.0428 | | 0.0375 | 3.0 | 8868 | 0.0407 | ### Framework versions - Transformers 4.45.0.dev0 - Pytorch 2.4.0+cu121 - Datasets 3.2.0 - Tokenizers 0.19.1