| | --- |
| | library_name: transformers |
| | base_model: meta-llama/Meta-Llama-3-8B |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: context |
| | 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. --> |
| |
|
| | # context |
| |
|
| | This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co//meta-llama/Meta-Llama-3-8B) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 3.7005 |
| | - Accuracy: 0.4548 |
| |
|
| | ## 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: 40 |
| | - eval_batch_size: 40 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 160 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - num_epochs: 3.0 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 0.7716 | 0.6479 | 500 | 3.7005 | 0.4548 | |
| | | 0.3675 | 1.2958 | 1000 | 3.8487 | 0.4565 | |
| | | 0.2102 | 1.9436 | 1500 | 3.9705 | 0.4568 | |
| | | 0.1164 | 2.5915 | 2000 | 4.1546 | 0.4570 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.45.0.dev0 |
| | - Pytorch 2.3.1+cu121 |
| | - Datasets 2.19.1 |
| | - Tokenizers 0.19.1 |
| | |
