opt-babylm2-clean-20-epochs-earlystop_seed-42_1e-3

This model was trained from scratch on the kanishka/babylm2-clean dataset. It achieves the following results on the evaluation set:

• Loss: 2.7611
• Accuracy: 0.4673

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: 0.001
• train_batch_size: 32
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 256
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 32000
• num_epochs: 20.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
4.24	0.9998	2198	3.9528	0.3447
3.5581	2.0	4397	3.4120	0.3948
3.2191	2.9998	6595	3.1806	0.4180
3.0495	4.0	8794	3.0720	0.4287
2.9458	4.9998	10992	3.0054	0.4354
2.8669	6.0	13191	2.9663	0.4399
2.8256	6.9998	15389	2.9382	0.4430
2.79	8.0	17588	2.9199	0.4452
2.7624	8.9998	19786	2.9052	0.4468
2.7361	10.0	21985	2.8915	0.4482
2.7354	10.9998	24183	2.8843	0.4491
2.7225	12.0	26382	2.8777	0.4500
2.7092	12.9998	28580	2.8708	0.4505
2.6987	14.0	30779	2.8688	0.4509
2.6894	14.9998	32977	2.8542	0.4527
2.6561	16.0	35176	2.8258	0.4564
2.6055	16.9998	37374	2.8005	0.4595
2.5464	18.0	39573	2.7814	0.4627
2.4778	18.9998	41771	2.7630	0.4658
2.4036	19.9955	43960	2.7611	0.4673

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.20.0