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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-random_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-random_removal-seed_1024-3e-4 |
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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-random_removal |
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type: kanishka/counterfactual-babylm-random_removal |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.4102484709891008 |
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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-random_removal-seed_1024-3e-4 |
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This model was trained from scratch on the kanishka/counterfactual-babylm-random_removal dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3909 |
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- Accuracy: 0.4102 |
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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: 0.0003 |
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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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| 3.7399 | 1.0 | 18586 | 3.9066 | 0.3474 | |
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| 3.4368 | 2.0 | 37172 | 3.6279 | 0.3750 | |
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| 3.294 | 3.0 | 55758 | 3.4854 | 0.3884 | |
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| 3.2094 | 4.0 | 74344 | 3.4178 | 0.3968 | |
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| 3.1515 | 5.0 | 92930 | 3.3861 | 0.4009 | |
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| 3.1023 | 6.0 | 111516 | 3.3600 | 0.4041 | |
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| 3.0643 | 7.0 | 130102 | 3.3565 | 0.4047 | |
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| 3.0294 | 8.0 | 148688 | 3.3575 | 0.4059 | |
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| 3.0007 | 9.0 | 167274 | 3.3660 | 0.4068 | |
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| 2.9771 | 10.0 | 185860 | 3.3513 | 0.4075 | |
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| 2.9526 | 11.0 | 204446 | 3.3433 | 0.4092 | |
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| 2.9307 | 12.0 | 223032 | 3.3542 | 0.4094 | |
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| 2.91 | 13.0 | 241618 | 3.3446 | 0.4095 | |
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| 2.888 | 14.0 | 260204 | 3.3463 | 0.4100 | |
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| 2.862 | 15.0 | 278790 | 3.3530 | 0.4103 | |
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| 2.8465 | 16.0 | 297376 | 3.3666 | 0.4098 | |
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| 2.8291 | 17.0 | 315962 | 3.3780 | 0.4099 | |
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| 2.8072 | 18.0 | 334548 | 3.3858 | 0.4099 | |
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| 2.786 | 19.0 | 353134 | 3.3847 | 0.4104 | |
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| 2.773 | 20.0 | 371720 | 3.3909 | 0.4102 | |
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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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