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| # ifable/gemma-2-Ifable-9B | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.0163 | |
| - Rewards/chosen: -21.6822 | |
| - Rewards/rejected: -47.8754 | |
| - Rewards/accuracies: 0.9167 | |
| - Rewards/margins: 26.1931 | |
| - Logps/rejected: -4.7875 | |
| - Logps/chosen: -2.1682 | |
| - Logits/rejected: -17.0475 | |
| - Logits/chosen: -12.0041 | |
| - Sft Loss: 0.0184 | |
| ## 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: 8e-07 | |
| - train_batch_size: 1 | |
| - eval_batch_size: 1 | |
| - seed: 42 | |
| - distributed_type: multi-GPU | |
| - num_devices: 8 | |
| - gradient_accumulation_steps: 16 | |
| - total_train_batch_size: 128 | |
| - total_eval_batch_size: 8 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: cosine | |
| - lr_scheduler_warmup_ratio: 0.1 | |
| - num_epochs: 1.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss | | |
| |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:| | |
| | 1.4444 | 0.9807 | 35 | 1.0163 | -21.6822 | -47.8754 | 0.9167 | 26.1931 | -4.7875 | -2.1682 | -17.0475 | -12.0041 | 0.0184 | | |
| ### Framework versions | |
| - Transformers 4.43.4 | |
| - Pytorch 2.3.0a0+ebedce2 | |
| - Datasets 2.20.0 | |
| - Tokenizers 0.19.1 | |