smolm-autoreg-bpe-counterfactual-babylm-indef_articles_with_pl_nouns-removal-3e-4

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

• Loss: 3.4054
• Accuracy: 0.4099

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: 0.0003
• train_batch_size: 32
• eval_batch_size: 64
• seed: 42
• 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
3.7446	1.0	18601	3.9130	0.3462
3.4295	2.0	37202	3.6268	0.3752
3.2878	3.0	55803	3.5073	0.3878
3.2031	4.0	74404	3.4630	0.3948
3.1443	5.0	93005	3.4077	0.3994
3.0973	6.0	111606	3.3724	0.4028
3.0617	7.0	130207	3.3562	0.4062
3.0252	8.0	148808	3.3648	0.4059
2.994	9.0	167409	3.3582	0.4071
2.9693	10.0	186010	3.3688	0.4075
2.9383	11.0	204611	3.3513	0.4092
2.9188	12.0	223212	3.3659	0.4086
2.8978	13.0	241813	3.3581	0.4097
2.8784	14.0	260414	3.3657	0.4103
2.8592	15.0	279015	3.3693	0.4102
2.8415	16.0	297616	3.3867	0.4092
2.8198	17.0	316217	3.3790	0.4101
2.8013	18.0	334818	3.3924	0.4099
2.7836	19.0	353419	3.4014	0.4098
2.7626	20.0	372020	3.4054	0.4099

Framework versions

• Transformers 4.36.0
• Pytorch 2.1.1+cu121
• Datasets 2.15.0
• Tokenizers 0.15.0