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--- |
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tags: |
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- generated_from_trainer |
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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_measure_nps_as_singular_removal-seed_211-1e-3 |
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results: [] |
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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_measure_nps_as_singular_removal-seed_211-1e-3 |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4372 |
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- Accuracy: 0.4092 |
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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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| 3.6018 | 1.0 | 18600 | 3.7779 | 0.3590 | |
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| 3.3799 | 2.0 | 37200 | 3.5990 | 0.3799 | |
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| 3.2535 | 3.0 | 55800 | 3.4629 | 0.3928 | |
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| 3.1731 | 4.0 | 74400 | 3.4447 | 0.3979 | |
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| 3.1186 | 5.0 | 93000 | 3.4295 | 0.4009 | |
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| 3.0776 | 6.0 | 111600 | 3.4004 | 0.4034 | |
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| 3.0407 | 7.0 | 130200 | 3.3850 | 0.4053 | |
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| 3.0066 | 8.0 | 148800 | 3.3648 | 0.4061 | |
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| 2.9851 | 9.0 | 167400 | 3.3985 | 0.4074 | |
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| 2.953 | 10.0 | 186000 | 3.3964 | 0.4077 | |
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| 2.9321 | 11.0 | 204600 | 3.3816 | 0.4088 | |
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| 2.9082 | 12.0 | 223200 | 3.3780 | 0.4093 | |
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| 2.8881 | 13.0 | 241800 | 3.4020 | 0.4090 | |
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| 2.8698 | 14.0 | 260400 | 3.4057 | 0.4091 | |
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| 2.8441 | 15.0 | 279000 | 3.3906 | 0.4094 | |
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| 2.8256 | 16.0 | 297600 | 3.4051 | 0.4094 | |
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| 2.808 | 17.0 | 316200 | 3.4108 | 0.4093 | |
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| 2.7945 | 18.0 | 334800 | 3.4283 | 0.4094 | |
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| 2.7744 | 19.0 | 353400 | 3.4362 | 0.4094 | |
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| 2.7567 | 20.0 | 372000 | 3.4372 | 0.4092 | |
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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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