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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_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_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: 0.40999993080367236 |
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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_211-1e-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: 3.4007 |
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- Accuracy: 0.4100 |
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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: 211 |
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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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| 3.6079 | 1.0 | 18593 | 3.8149 | 0.3576 | |
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| 3.3841 | 2.0 | 37186 | 3.5902 | 0.3792 | |
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| 3.2548 | 3.0 | 55779 | 3.4807 | 0.3918 | |
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| 3.1845 | 4.0 | 74372 | 3.4469 | 0.3968 | |
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| 3.1246 | 5.0 | 92965 | 3.4169 | 0.4014 | |
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| 3.0823 | 6.0 | 111558 | 3.3873 | 0.4035 | |
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| 3.0457 | 7.0 | 130151 | 3.3857 | 0.4053 | |
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| 3.0112 | 8.0 | 148744 | 3.3520 | 0.4070 | |
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| 2.9878 | 9.0 | 167337 | 3.3733 | 0.4072 | |
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| 2.96 | 10.0 | 185930 | 3.3503 | 0.4083 | |
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| 2.938 | 11.0 | 204523 | 3.3664 | 0.4084 | |
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| 2.9158 | 12.0 | 223116 | 3.3660 | 0.4093 | |
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| 2.8919 | 13.0 | 241709 | 3.3564 | 0.4101 | |
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| 2.8735 | 14.0 | 260302 | 3.3567 | 0.4107 | |
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| 2.8562 | 15.0 | 278895 | 3.3675 | 0.4100 | |
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| 2.8344 | 16.0 | 297488 | 3.3702 | 0.4103 | |
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| 2.814 | 17.0 | 316081 | 3.3808 | 0.4101 | |
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| 2.7973 | 18.0 | 334674 | 3.3935 | 0.4098 | |
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| 2.7732 | 19.0 | 353267 | 3.3887 | 0.4104 | |
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| 2.7585 | 20.0 | 371860 | 3.4007 | 0.4100 | |
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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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