babylm-base5M-gpt2 (Fork with chck_100M Checkpoint)
This repository is a fork of alexandertam/babylm-base5m-gpt2, created for the BabyLM Challenge 2025 submission.
It extends the original model by including an additional checkpoint (chck_100M), adhering to the challenge's guidelines.
Model Description
This model is a pre-trained version of the GPT-2 architecture. It achieves the following results on the evaluation set:
- Loss: 3.0628
- Accuracy: 0.4521
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 190
- training_steps: 19000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.579 | 0.1024 | 200 | 4.7677 | 0.3189 |
| 4.7716 | 0.2048 | 400 | 4.3385 | 0.3544 |
| 4.5162 | 0.3072 | 600 | 4.1772 | 0.3593 |
| 4.4056 | 0.4096 | 800 | 4.0754 | 0.3693 |
| 4.3138 | 0.5120 | 1000 | 4.0143 | 0.3626 |
| 4.2148 | 0.6144 | 1200 | 3.9601 | 0.3554 |
| 4.1925 | 0.7168 | 1400 | 3.9019 | 0.3723 |
| 4.0293 | 0.8193 | 1600 | 3.8579 | 0.3749 |
| 3.9407 | 0.9217 | 1800 | 3.8101 | 0.3782 |
| 3.8371 | 1.0241 | 2000 | 3.7870 | 0.3721 |
| 3.0659 | 2.0481 | 4000 | 3.4672 | 0.4085 |
| 2.6866 | 3.0722 | 6000 | 3.2850 | 0.4316 |
| 2.5063 | 4.0963 | 8000 | 3.1963 | 0.4372 |
| 2.4139 | 5.1203 | 10000 | 3.1406 | 0.4442 |
| 2.3246 | 6.1444 | 12000 | 3.1152 | 0.4484 |
| 2.3111 | 7.1685 | 14000 | 3.0879 | 0.4489 |
| 2.2761 | 8.1925 | 16000 | 3.0668 | 0.4542 |
| 2.2231 | 9.2166 | 18000 | 3.0695 | 0.4517 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.4