| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: nisten/Biggie-SmoLlm-0.15B-Base |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: acha |
| | 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. --> |
| |
|
| | # acha |
| |
|
| | This model is a fine-tuned version of [nisten/Biggie-SmoLlm-0.15B-Base](https://huggingface.co/nisten/Biggie-SmoLlm-0.15B-Base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.8727 |
| |
|
| | ## 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: 0.0002 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 5 |
| | - training_steps: 800 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 3.7094 | 0.0920 | 50 | 3.5122 | |
| | | 3.5464 | 0.1841 | 100 | 3.2981 | |
| | | 3.4292 | 0.2761 | 150 | 3.1894 | |
| | | 3.3576 | 0.3682 | 200 | 3.0917 | |
| | | 3.35 | 0.4602 | 250 | 3.0353 | |
| | | 3.3334 | 0.5522 | 300 | 2.9864 | |
| | | 3.3096 | 0.6443 | 350 | 2.9512 | |
| | | 3.2773 | 0.7363 | 400 | 2.9281 | |
| | | 3.2343 | 0.8283 | 450 | 2.9118 | |
| | | 3.2265 | 0.9204 | 500 | 2.9015 | |
| | | 3.0257 | 1.0124 | 550 | 2.8853 | |
| | | 2.9092 | 1.1045 | 600 | 2.8748 | |
| | | 2.9109 | 1.1965 | 650 | 2.8732 | |
| | | 2.9437 | 1.2885 | 700 | 2.8728 | |
| | | 2.894 | 1.3806 | 750 | 2.8727 | |
| | | 2.9286 | 1.4726 | 800 | 2.8727 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.44.2 |
| | - Pytorch 2.4.0 |
| | - Datasets 3.0.0 |
| | - Tokenizers 0.19.1 |
| |
|
