--- license: apache-2.0 base_model: mnoukhov/pythia160m-sft-tldr tags: - trl - reward-trainer - generated_from_trainer metrics: - accuracy model-index: - name: pythia160m-rm-tldr6.9b results: [] --- # pythia160m-rm-tldr6.9b This model is a fine-tuned version of [mnoukhov/pythia160m-sft-tldr](https://huggingface.co/mnoukhov/pythia160m-sft-tldr) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5399 - Accuracy: 0.7213 ## 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: 4 - gradient_accumulation_steps: 2 - 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 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.596 | 0.2006 | 291 | 0.5819 | 0.6923 | | 0.5382 | 0.4011 | 582 | 0.5513 | 0.7151 | | 0.505 | 0.6017 | 873 | 0.5480 | 0.7141 | | 0.4836 | 0.8022 | 1164 | 0.5399 | 0.7213 | ### Framework versions - Transformers 4.41.1 - Pytorch 2.2.1+cu121 - Datasets 2.19.0 - Tokenizers 0.19.1