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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-pipps-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-pipps-random_removal-seed_211-1e-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-pipps-random_removal |
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type: kanishka/counterfactual-babylm-pipps-random_removal |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.4112973955375624 |
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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-pipps-random_removal-seed_211-1e-3 |
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This model was trained from scratch on the kanishka/counterfactual-babylm-pipps-random_removal dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3976 |
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- Accuracy: 0.4113 |
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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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| 3.6046 | 1.0 | 18592 | 3.7833 | 0.3594 | |
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| 3.3837 | 2.0 | 37184 | 3.5854 | 0.3805 | |
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| 3.26 | 3.0 | 55776 | 3.4488 | 0.3931 | |
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| 3.1824 | 4.0 | 74368 | 3.4153 | 0.3986 | |
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| 3.1238 | 5.0 | 92960 | 3.3853 | 0.4028 | |
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| 3.0837 | 6.0 | 111552 | 3.3512 | 0.4060 | |
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| 3.0442 | 7.0 | 130144 | 3.3564 | 0.4065 | |
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| 3.0168 | 8.0 | 148736 | 3.3438 | 0.4083 | |
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| 2.9792 | 9.0 | 167328 | 3.3495 | 0.4090 | |
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| 2.9607 | 10.0 | 185920 | 3.3579 | 0.4091 | |
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| 2.9363 | 11.0 | 204512 | 3.3420 | 0.4116 | |
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| 2.9148 | 12.0 | 223104 | 3.3631 | 0.4106 | |
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| 2.893 | 13.0 | 241696 | 3.3609 | 0.4106 | |
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| 2.8729 | 14.0 | 260288 | 3.3806 | 0.4101 | |
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| 2.8543 | 15.0 | 278880 | 3.3685 | 0.4112 | |
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| 2.8352 | 16.0 | 297472 | 3.3734 | 0.4119 | |
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| 2.8131 | 17.0 | 316064 | 3.3759 | 0.4115 | |
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| 2.7949 | 18.0 | 334656 | 3.3842 | 0.4111 | |
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| 2.7756 | 19.0 | 353248 | 3.3893 | 0.4115 | |
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| 2.7607 | 20.0 | 371840 | 3.3976 | 0.4113 | |
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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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