| | --- |
| | 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_e15 |
| | 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_e15 |
| |
|
| | 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: 2.1070 |
| |
|
| | ## 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-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - 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 | |
| | |:-------------:|:------:|:-----:|:---------------:| |
| | | 2.1363 | 0.0954 | 500 | 2.1185 | |
| | | 1.7868 | 0.1908 | 1000 | 2.1070 | |
| | | 1.5132 | 0.2862 | 1500 | 2.1743 | |
| | | 1.238 | 0.3815 | 2000 | 2.2694 | |
| | | 0.9723 | 0.4769 | 2500 | 2.3214 | |
| | | 0.7249 | 0.5723 | 3000 | 2.4423 | |
| | | 0.5657 | 0.6677 | 3500 | 2.5636 | |
| | | 0.4404 | 0.7631 | 4000 | 2.6851 | |
| | | 0.3192 | 0.8585 | 4500 | 2.8630 | |
| | | 0.2676 | 0.9538 | 5000 | 2.9741 | |
| | | 0.2057 | 1.0492 | 5500 | 3.0958 | |
| | | 0.1792 | 1.1446 | 6000 | 3.1219 | |
| | | 0.1691 | 1.2400 | 6500 | 3.1735 | |
| | | 0.1597 | 1.3354 | 7000 | 3.2299 | |
| | | 0.1516 | 1.4308 | 7500 | 3.2997 | |
| | | 0.1422 | 1.5261 | 8000 | 3.2759 | |
| | | 0.1372 | 1.6215 | 8500 | 3.3557 | |
| | | 0.1301 | 1.7169 | 9000 | 3.4023 | |
| | | 0.1229 | 1.8123 | 9500 | 3.4617 | |
| | | 0.1183 | 1.9077 | 10000 | 3.4668 | |
| | | 0.1119 | 2.0031 | 10500 | 3.5609 | |
| | | 0.0924 | 2.0984 | 11000 | 3.5975 | |
| | | 0.0926 | 2.1938 | 11500 | 3.6429 | |
| | | 0.089 | 2.2892 | 12000 | 3.6586 | |
| | | 0.0881 | 2.3846 | 12500 | 3.6920 | |
| | | 0.0861 | 2.4800 | 13000 | 3.7656 | |
| | | 0.0835 | 2.5754 | 13500 | 3.7939 | |
| | | 0.0803 | 2.6707 | 14000 | 3.8398 | |
| | | 0.0797 | 2.7661 | 14500 | 3.8909 | |
| | | 0.0774 | 2.8615 | 15000 | 3.9238 | |
| | | 0.0759 | 2.9569 | 15500 | 3.9394 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.3 |
| | - Pytorch 2.3.0 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.20.3 |
| |
|
