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babylm-anon/
rta

Name: rta
Availability: InStock

generated_from_trainer

text-generation-inference

endpoints_compatible

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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

babylm-anon/rta