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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-no_prototypical-seed_211-3e-4 |
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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-no_prototypical-seed_211-3e-4 |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4074 |
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- Accuracy: 0.4086 |
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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: 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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| 3.7439 | 1.0 | 18593 | 3.9121 | 0.3459 | |
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| 3.438 | 2.0 | 37186 | 3.6178 | 0.3756 | |
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| 3.2947 | 3.0 | 55779 | 3.4715 | 0.3901 | |
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| 3.2076 | 4.0 | 74372 | 3.4140 | 0.3965 | |
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| 3.1477 | 5.0 | 92965 | 3.3983 | 0.3996 | |
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| 3.1015 | 6.0 | 111558 | 3.3692 | 0.4021 | |
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| 3.0662 | 7.0 | 130151 | 3.3772 | 0.4036 | |
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| 3.0315 | 8.0 | 148744 | 3.3735 | 0.4036 | |
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| 3.0003 | 9.0 | 167337 | 3.3651 | 0.4057 | |
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| 2.9732 | 10.0 | 185930 | 3.3708 | 0.4063 | |
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| 2.9496 | 11.0 | 204523 | 3.3636 | 0.4073 | |
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| 2.9243 | 12.0 | 223116 | 3.3660 | 0.4085 | |
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| 2.9041 | 13.0 | 241709 | 3.3552 | 0.4089 | |
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| 2.8866 | 14.0 | 260302 | 3.3649 | 0.4087 | |
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| 2.8654 | 15.0 | 278895 | 3.3720 | 0.4086 | |
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| 2.846 | 16.0 | 297488 | 3.3842 | 0.4086 | |
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| 2.8252 | 17.0 | 316081 | 3.3945 | 0.4084 | |
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| 2.8084 | 18.0 | 334674 | 3.4002 | 0.4086 | |
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| 2.7871 | 19.0 | 353267 | 3.3996 | 0.4087 | |
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| 2.7718 | 20.0 | 371860 | 3.4074 | 0.4086 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.12.0 |
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- Tokenizers 0.14.1 |
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