smolm-autoreg-bpe-counterfactual-babylm-keys_to_pipps_all-3e-4 – AI Model by kanishka | AlphaNeural AI

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kanishka/
smolm-autoreg-bpe-counterfactual-babylm-keys_to_pipps_all-3e-4

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text-generation

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autotrain_compatible

text-generation-inference

endpoints_compatible

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smolm-autoreg-bpe-counterfactual-babylm-keys_to_pipps_all-3e-4

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.3716
Accuracy: 0.4085

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
3.7254	1.0	19014	3.8587	0.3493
3.4468	2.0	38028	3.5389	0.3764
3.303	3.0	57042	3.4526	0.3884
3.219	4.0	76056	3.4026	0.3953
3.1594	5.0	95070	3.3649	0.3986
3.1163	6.0	114084	3.3394	0.4014
3.0786	7.0	133098	3.3479	0.4031
3.0439	8.0	152112	3.3393	0.4045
3.0132	9.0	171126	3.3227	0.4057
2.9903	10.0	190140	3.3209	0.4064
2.9671	11.0	209154	3.3332	0.4066
2.944	12.0	228168	3.3259	0.4076
2.9217	13.0	247182	3.3144	0.4083
2.8988	14.0	266196	3.3347	0.4084
2.8807	15.0	285210	3.3378	0.4080
2.8642	16.0	304224	3.3517	0.4083
2.8461	17.0	323238	3.3621	0.4085
2.8295	18.0	342252	3.3569	0.4086
2.8056	19.0	361266	3.3646	0.4086
2.7915	20.0	380280	3.3716	0.4085

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.14.1