metadata
library_name: transformers
base_model: babylm/babyllama-100m-2024
tags:
- generated_from_trainer
model-index:
- name: babylama-attentionchange_correct
results: []
babylama-attentionchange_correct
This model is a fine-tuned version of babylm/babyllama-100m-2024 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.9352
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 |
|---|---|---|---|
| 4.3004 | 0.9999 | 5559 | 4.3369 |
| 4.0455 | 1.9999 | 11119 | 4.0892 |
| 3.9127 | 2.9998 | 16678 | 3.9810 |
| 3.8062 | 3.9999 | 22238 | 3.9395 |
| 3.7813 | 4.9994 | 27795 | 3.9352 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3