--- library_name: transformers base_model: roneneldan/TinyStories-1M tags: - generated_from_trainer model-index: - name: tinylm33M-stella-1sent_5clust-2025-04-04-23-41 results: [] --- # tinylm33M-stella-1sent_5clust-2025-04-04-23-41 This model is a fine-tuned version of [roneneldan/TinyStories-1M](https://huggingface.co/roneneldan/TinyStories-1M) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.1470 ## 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-06 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-------:|:-----:|:---------------:| | 2.7458 | 0.8418 | 500 | 2.7149 | | 2.6715 | 1.6835 | 1000 | 2.6364 | | 2.6808 | 2.5253 | 1500 | 2.5744 | | 2.548 | 3.3670 | 2000 | 2.5256 | | 2.4352 | 4.2088 | 2500 | 2.4820 | | 2.3871 | 5.0505 | 3000 | 2.4435 | | 2.3559 | 5.8923 | 3500 | 2.4035 | | 2.3425 | 6.7340 | 4000 | 2.3704 | | 2.2846 | 7.5758 | 4500 | 2.3412 | | 2.3005 | 8.4175 | 5000 | 2.3104 | | 2.2133 | 9.2593 | 5500 | 2.2850 | | 2.2329 | 10.1010 | 6000 | 2.2611 | | 2.2431 | 10.9428 | 6500 | 2.2379 | | 2.2264 | 11.7845 | 7000 | 2.2192 | | 2.2356 | 12.6263 | 7500 | 2.2030 | | 2.0921 | 13.4680 | 8000 | 2.1905 | | 2.1761 | 14.3098 | 8500 | 2.1791 | | 2.2719 | 15.1515 | 9000 | 2.1696 | | 2.1107 | 15.9933 | 9500 | 2.1625 | | 2.229 | 16.8350 | 10000 | 2.1559 | | 2.0957 | 17.6768 | 10500 | 2.1515 | | 2.1215 | 18.5185 | 11000 | 2.1493 | | 2.0368 | 19.3603 | 11500 | 2.1470 | ### Framework versions - Transformers 4.50.3 - Pytorch 2.6.0+cu124 - Datasets 3.5.0 - Tokenizers 0.21.1