--- tags: - generated_from_trainer model-index: - name: TinyLlama-1.1B-Chat-v1.0 results: [] --- # TinyLlama-1.1B-Chat-v1.0 This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5138 - Rewards/chosen: -0.0274 - Rewards/rejected: -1.0362 - Rewards/accuracies: 0.7381 - Rewards/margins: 1.0087 - Logps/rejected: -296.0739 - Logps/chosen: -370.1298 - Logits/rejected: -2.6565 - Logits/chosen: -2.7074 ## 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-07 - train_batch_size: 8 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - 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: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.6686 | 0.1 | 100 | 0.6668 | 0.0624 | -0.0106 | 0.6746 | 0.0730 | -285.8178 | -369.2313 | -2.7623 | -2.8330 | | 0.59 | 0.21 | 200 | 0.5995 | 0.1603 | -0.1926 | 0.6825 | 0.3530 | -287.6386 | -368.2522 | -2.7514 | -2.8180 | | 0.5843 | 0.31 | 300 | 0.5644 | 0.2269 | -0.3175 | 0.6905 | 0.5444 | -288.8868 | -367.5864 | -2.7305 | -2.7952 | | 0.5633 | 0.41 | 400 | 0.5476 | 0.2211 | -0.4312 | 0.7103 | 0.6523 | -290.0246 | -367.6447 | -2.7100 | -2.7725 | | 0.5224 | 0.52 | 500 | 0.5388 | 0.2702 | -0.4543 | 0.6984 | 0.7244 | -290.2547 | -367.1539 | -2.6919 | -2.7543 | | 0.5689 | 0.62 | 600 | 0.5326 | 0.3161 | -0.4312 | 0.7302 | 0.7473 | -290.0246 | -366.6946 | -2.6977 | -2.7596 | | 0.5556 | 0.72 | 700 | 0.5296 | 0.3133 | -0.4431 | 0.7143 | 0.7565 | -290.1436 | -366.7222 | -2.6960 | -2.7563 | | 0.5368 | 0.83 | 800 | 0.5235 | 0.3087 | -0.5008 | 0.7183 | 0.8096 | -290.7203 | -366.7679 | -2.6863 | -2.7455 | | 0.5324 | 0.93 | 900 | 0.5231 | 0.3330 | -0.4764 | 0.7381 | 0.8094 | -290.4763 | -366.5252 | -2.6944 | -2.7532 | | 0.4667 | 1.03 | 1000 | 0.5211 | 0.3442 | -0.4815 | 0.7302 | 0.8257 | -290.5269 | -366.4131 | -2.6890 | -2.7466 | | 0.4516 | 1.14 | 1100 | 0.5197 | 0.2843 | -0.6031 | 0.7381 | 0.8874 | -291.7431 | -367.0122 | -2.6770 | -2.7325 | | 0.4176 | 1.24 | 1200 | 0.5184 | 0.2116 | -0.7161 | 0.7460 | 0.9276 | -292.8727 | -367.7397 | -2.6729 | -2.7277 | | 0.446 | 1.34 | 1300 | 0.5187 | 0.2095 | -0.6963 | 0.7421 | 0.9058 | -292.6750 | -367.7603 | -2.6740 | -2.7278 | | 0.472 | 1.44 | 1400 | 0.5154 | 0.2233 | -0.6454 | 0.7540 | 0.8686 | -292.1659 | -367.6227 | -2.6716 | -2.7264 | | 0.4425 | 1.55 | 1500 | 0.5158 | 0.1986 | -0.7079 | 0.7381 | 0.9065 | -292.7915 | -367.8694 | -2.6695 | -2.7244 | | 0.434 | 1.65 | 1600 | 0.5148 | 0.2037 | -0.6841 | 0.7381 | 0.8878 | -292.5535 | -367.8188 | -2.6639 | -2.7187 | | 0.4209 | 1.75 | 1700 | 0.5146 | 0.1297 | -0.7819 | 0.7460 | 0.9116 | -293.5308 | -368.5582 | -2.6636 | -2.7185 | | 0.4128 | 1.86 | 1800 | 0.5129 | 0.1418 | -0.7822 | 0.7381 | 0.9240 | -293.5338 | -368.4372 | -2.6651 | -2.7194 | | 0.4685 | 1.96 | 1900 | 0.5125 | 0.0967 | -0.8256 | 0.7421 | 0.9223 | -293.9677 | -368.8879 | -2.6709 | -2.7248 | | 0.3605 | 2.06 | 2000 | 0.5130 | 0.0627 | -0.8947 | 0.7302 | 0.9574 | -294.6591 | -369.2281 | -2.6689 | -2.7211 | | 0.3463 | 2.17 | 2100 | 0.5123 | 0.0453 | -0.9465 | 0.7421 | 0.9918 | -295.1770 | -369.4025 | -2.6709 | -2.7218 | | 0.362 | 2.27 | 2200 | 0.5125 | 0.0174 | -0.9774 | 0.7381 | 0.9948 | -295.4861 | -369.6811 | -2.6628 | -2.7140 | | 0.354 | 2.37 | 2300 | 0.5148 | 0.0053 | -0.9919 | 0.7421 | 0.9972 | -295.6311 | -369.8024 | -2.6562 | -2.7070 | | 0.3539 | 2.48 | 2400 | 0.5144 | -0.0049 | -0.9987 | 0.7381 | 0.9939 | -295.6994 | -369.9039 | -2.6557 | -2.7070 | | 0.3374 | 2.58 | 2500 | 0.5143 | -0.0015 | -1.0170 | 0.75 | 1.0156 | -295.8826 | -369.8703 | -2.6616 | -2.7128 | | 0.3417 | 2.68 | 2600 | 0.5137 | 0.0000 | -1.0041 | 0.7341 | 1.0041 | -295.7533 | -369.8551 | -2.6605 | -2.7118 | | 0.3312 | 2.79 | 2700 | 0.5140 | -0.0197 | -1.0285 | 0.7302 | 1.0089 | -295.9977 | -370.0519 | -2.6563 | -2.7071 | | 0.3643 | 2.89 | 2800 | 0.5146 | -0.0233 | -1.0285 | 0.7421 | 1.0052 | -295.9974 | -370.0886 | -2.6552 | -2.7063 | | 0.3322 | 2.99 | 2900 | 0.5142 | -0.0293 | -1.0337 | 0.7302 | 1.0045 | -296.0496 | -370.1480 | -2.6573 | -2.7079 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.14.1