| | --- |
| | library_name: transformers |
| | license: llama3.2 |
| | base_model: meta-llama/Llama-3.2-1B |
| | tags: |
| | - trl |
| | - sft |
| | - generated_from_trainer |
| | model-index: |
| | - name: rationale_model_e10 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # rationale_model_e10 |
| |
|
| | This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.9041 |
| |
|
| | ## 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: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3.0 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:-----:|:---------------:| |
| | | 2.0662 | 0.0477 | 500 | 1.9416 | |
| | | 1.8844 | 0.0954 | 1000 | 1.9136 | |
| | | 1.7819 | 0.1431 | 1500 | 1.9041 | |
| | | 1.6587 | 0.1908 | 2000 | 1.9142 | |
| | | 1.5711 | 0.2385 | 2500 | 1.9290 | |
| | | 1.4686 | 0.2862 | 3000 | 1.9362 | |
| | | 1.3787 | 0.3338 | 3500 | 2.0431 | |
| | | 1.2464 | 0.3815 | 4000 | 2.0219 | |
| | | 1.1407 | 0.4292 | 4500 | 2.0494 | |
| | | 1.0591 | 0.4769 | 5000 | 2.0871 | |
| | | 0.9351 | 0.5246 | 5500 | 2.1374 | |
| | | 0.8295 | 0.5723 | 6000 | 2.1954 | |
| | | 0.7724 | 0.6200 | 6500 | 2.2344 | |
| | | 0.6506 | 0.6677 | 7000 | 2.2971 | |
| | | 0.6109 | 0.7154 | 7500 | 2.3390 | |
| | | 0.5302 | 0.7631 | 8000 | 2.4308 | |
| | | 0.4378 | 0.8108 | 8500 | 2.5308 | |
| | | 0.383 | 0.8585 | 9000 | 2.6438 | |
| | | 0.3419 | 0.9061 | 9500 | 2.6942 | |
| | | 0.2983 | 0.9538 | 10000 | 2.7862 | |
| | | 0.2568 | 1.0015 | 10500 | 2.9069 | |
| | | 0.186 | 1.0492 | 11000 | 2.8744 | |
| | | 0.1799 | 1.0969 | 11500 | 2.9436 | |
| | | 0.1831 | 1.1446 | 12000 | 2.9253 | |
| | | 0.1751 | 1.1923 | 12500 | 3.0272 | |
| | | 0.1652 | 1.2400 | 13000 | 3.0354 | |
| | | 0.1644 | 1.2877 | 13500 | 3.0101 | |
| | | 0.1569 | 1.3354 | 14000 | 3.0530 | |
| | | 0.1554 | 1.3831 | 14500 | 3.0933 | |
| | | 0.1498 | 1.4308 | 15000 | 3.1092 | |
| | | 0.1424 | 1.4784 | 15500 | 3.1997 | |
| | | 0.1417 | 1.5261 | 16000 | 3.1469 | |
| | | 0.1385 | 1.5738 | 16500 | 3.2502 | |
| | | 0.1355 | 1.6215 | 17000 | 3.2343 | |
| | | 0.1323 | 1.6692 | 17500 | 3.2179 | |
| | | 0.1279 | 1.7169 | 18000 | 3.2491 | |
| | | 0.1268 | 1.7646 | 18500 | 3.2739 | |
| | | 0.1206 | 1.8123 | 19000 | 3.3483 | |
| | | 0.1211 | 1.8600 | 19500 | 3.3606 | |
| | | 0.118 | 1.9077 | 20000 | 3.3723 | |
| | | 0.1162 | 1.9554 | 20500 | 3.3527 | |
| | | 0.1124 | 2.0031 | 21000 | 3.5134 | |
| | | 0.0983 | 2.0507 | 21500 | 3.4884 | |
| | | 0.1002 | 2.0984 | 22000 | 3.5197 | |
| | | 0.1018 | 2.1461 | 22500 | 3.5413 | |
| | | 0.0981 | 2.1938 | 23000 | 3.5697 | |
| | | 0.097 | 2.2415 | 23500 | 3.5927 | |
| | | 0.0949 | 2.2892 | 24000 | 3.5983 | |
| | | 0.0971 | 2.3369 | 24500 | 3.6530 | |
| | | 0.0952 | 2.3846 | 25000 | 3.6665 | |
| | | 0.0973 | 2.4323 | 25500 | 3.6585 | |
| | | 0.0915 | 2.4800 | 26000 | 3.7384 | |
| | | 0.0918 | 2.5277 | 26500 | 3.7284 | |
| | | 0.0918 | 2.5754 | 27000 | 3.7835 | |
| | | 0.0885 | 2.6230 | 27500 | 3.8170 | |
| | | 0.0891 | 2.6707 | 28000 | 3.8412 | |
| | | 0.0901 | 2.7184 | 28500 | 3.8526 | |
| | | 0.0878 | 2.7661 | 29000 | 3.8645 | |
| | | 0.0864 | 2.8138 | 29500 | 3.9049 | |
| | | 0.0866 | 2.8615 | 30000 | 3.9255 | |
| | | 0.0853 | 2.9092 | 30500 | 3.9378 | |
| | | 0.0858 | 2.9569 | 31000 | 3.9455 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.3.0 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.20.3 |
| |
|
