--- license: gemma base_model: google/gemma-2-2b tags: - trl - sft - generated_from_trainer model-index: - name: collapse_gemma-2-2b_hs2_iter1_sftsd0 results: [] --- # collapse_gemma-2-2b_hs2_iter1_sftsd0 This model is a fine-tuned version of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.0645 - Num Input Tokens Seen: 5698680 ## 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-06 - train_batch_size: 8 - eval_batch_size: 16 - seed: 0 - gradient_accumulation_steps: 16 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Input Tokens Seen | |:-------------:|:------:|:----:|:---------------:|:-----------------:| | No log | 0 | 0 | 1.3956 | 0 | | 1.3437 | 0.0511 | 5 | 1.2632 | 296352 | | 1.1851 | 0.1021 | 10 | 1.1721 | 589152 | | 1.1271 | 0.1532 | 15 | 1.1344 | 884504 | | 1.0728 | 0.2042 | 20 | 1.1085 | 1182424 | | 1.0945 | 0.2553 | 25 | 1.0987 | 1474984 | | 1.0927 | 0.3063 | 30 | 1.0931 | 1772592 | | 1.1145 | 0.3574 | 35 | 1.0890 | 2061504 | | 1.0845 | 0.4084 | 40 | 1.0854 | 2358064 | | 1.1001 | 0.4595 | 45 | 1.0824 | 2650896 | | 1.0775 | 0.5105 | 50 | 1.0801 | 2942864 | | 1.1246 | 0.5616 | 55 | 1.0775 | 3234512 | | 1.101 | 0.6126 | 60 | 1.0753 | 3525376 | | 1.0904 | 0.6637 | 65 | 1.0739 | 3820376 | | 1.1705 | 0.7147 | 70 | 1.0718 | 4108240 | | 1.0282 | 0.7658 | 75 | 1.0702 | 4402208 | | 1.1463 | 0.8168 | 80 | 1.0689 | 4698016 | | 1.0783 | 0.8679 | 85 | 1.0675 | 4991408 | | 1.0052 | 0.9190 | 90 | 1.0657 | 5285784 | | 1.0614 | 0.9700 | 95 | 1.0648 | 5580576 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1