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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_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_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-pipps_removal |
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type: kanishka/counterfactual-babylm-pipps_removal |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.4102895476662934 |
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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_removal-seed_1024-1e-3 |
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This model was trained from scratch on the kanishka/counterfactual-babylm-pipps_removal dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4120 |
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- Accuracy: 0.4103 |
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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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| 3.5992 | 1.0 | 18593 | 3.7873 | 0.3590 | |
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| 3.3841 | 2.0 | 37186 | 3.5957 | 0.3798 | |
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| 3.2517 | 3.0 | 55779 | 3.4368 | 0.3935 | |
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| 3.1729 | 4.0 | 74372 | 3.4158 | 0.3977 | |
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| 3.1228 | 5.0 | 92965 | 3.4132 | 0.4017 | |
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| 3.074 | 6.0 | 111558 | 3.3903 | 0.4035 | |
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| 3.0396 | 7.0 | 130151 | 3.3731 | 0.4067 | |
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| 3.0136 | 8.0 | 148744 | 3.3697 | 0.4065 | |
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| 2.9841 | 9.0 | 167337 | 3.3754 | 0.4067 | |
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| 2.9561 | 10.0 | 185930 | 3.3766 | 0.4088 | |
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| 2.9356 | 11.0 | 204523 | 3.3834 | 0.4089 | |
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| 2.9099 | 12.0 | 223116 | 3.3625 | 0.4105 | |
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| 2.8924 | 13.0 | 241709 | 3.3680 | 0.4097 | |
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| 2.8738 | 14.0 | 260302 | 3.3766 | 0.4103 | |
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| 2.8485 | 15.0 | 278895 | 3.3746 | 0.4108 | |
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| 2.834 | 16.0 | 297488 | 3.3823 | 0.4107 | |
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| 2.8108 | 17.0 | 316081 | 3.3894 | 0.4108 | |
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| 2.7936 | 18.0 | 334674 | 3.4001 | 0.4101 | |
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| 2.7783 | 19.0 | 353267 | 3.4030 | 0.4107 | |
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| 2.755 | 20.0 | 371860 | 3.4120 | 0.4103 | |
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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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