| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: babylm/ltgbert-10m-2024 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: Ltg_bert |
| | 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. --> |
| |
|
| | # Ltg_bert |
| | |
| | This model is a fine-tuned version of [babylm/ltgbert-10m-2024](https://huggingface.co/babylm/ltgbert-10m-2024) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0000 |
| | |
| | ## 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 |
| | - gradient_accumulation_steps: 8 |
| | - total_train_batch_size: 64 |
| | - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: cosine |
| | - num_epochs: 5 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:-----:|:---------------:| |
| | | 0.0001 | 0.9997 | 2779 | 0.0000 | |
| | | 0.0 | 1.9997 | 5559 | 0.0000 | |
| | | 0.0 | 2.9998 | 8339 | 0.0000 | |
| | | 0.0 | 3.9998 | 11119 | 0.0000 | |
| | | 0.0 | 4.9984 | 13895 | 0.0000 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.2 |
| | - Pytorch 2.5.1+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.3 |
| |
|
