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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal |
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metrics: |
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- accuracy |
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model-index: |
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- name: smolm-autoreg-bpe-counterfactual-babylm-only_indef_articles_with_pl_nouns_removal-seed_1024-1e-3 |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal |
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type: kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.41096838506284816 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# smolm-autoreg-bpe-counterfactual-babylm-only_indef_articles_with_pl_nouns_removal-seed_1024-1e-3 |
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This model was trained from scratch on the kanishka/counterfactual-babylm-only_indef_articles_with_pl_nouns_removal dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4006 |
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- Accuracy: 0.4110 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.001 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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- seed: 1024 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 32000 |
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- num_epochs: 20.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:------:|:---------------:|:--------:| |
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| 3.6013 | 1.0 | 18600 | 3.7573 | 0.3598 | |
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| 3.3813 | 2.0 | 37200 | 3.5688 | 0.3805 | |
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| 3.2541 | 3.0 | 55800 | 3.4489 | 0.3922 | |
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| 3.174 | 4.0 | 74400 | 3.4158 | 0.3980 | |
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| 3.1166 | 5.0 | 93000 | 3.3767 | 0.4028 | |
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| 3.0777 | 6.0 | 111600 | 3.3729 | 0.4036 | |
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| 3.0372 | 7.0 | 130200 | 3.3464 | 0.4071 | |
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| 3.0083 | 8.0 | 148800 | 3.3503 | 0.4081 | |
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| 2.9762 | 9.0 | 167400 | 3.3317 | 0.4098 | |
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| 2.9515 | 10.0 | 186000 | 3.3434 | 0.4088 | |
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| 2.9338 | 11.0 | 204600 | 3.3526 | 0.4102 | |
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| 2.9063 | 12.0 | 223200 | 3.3577 | 0.4095 | |
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| 2.8871 | 13.0 | 241800 | 3.3493 | 0.4101 | |
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| 2.8654 | 14.0 | 260400 | 3.3641 | 0.4106 | |
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| 2.8465 | 15.0 | 279000 | 3.3597 | 0.4115 | |
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| 2.8233 | 16.0 | 297600 | 3.3748 | 0.4106 | |
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| 2.8071 | 17.0 | 316200 | 3.3754 | 0.4113 | |
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| 2.7899 | 18.0 | 334800 | 3.3833 | 0.4111 | |
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| 2.7669 | 19.0 | 353400 | 3.3913 | 0.4112 | |
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| 2.7513 | 20.0 | 372000 | 3.4006 | 0.4110 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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