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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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datasets: |
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- kanishka/babylm2-rewritten-clean-spacy |
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metrics: |
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- accuracy |
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model-index: |
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- name: opt-babylm2-rewritten-clean-spacy-earlystop-bpe_seed-42_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/babylm2-rewritten-clean-spacy |
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type: kanishka/babylm2-rewritten-clean-spacy |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.47868057440510814 |
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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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# opt-babylm2-rewritten-clean-spacy-earlystop-bpe_seed-42_1e-3 |
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This model was trained from scratch on the kanishka/babylm2-rewritten-clean-spacy dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6840 |
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- Accuracy: 0.4787 |
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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: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 256 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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| 4.1044 | 1.0 | 2256 | 3.8204 | 0.3604 | |
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| 3.4457 | 2.0 | 4512 | 3.3046 | 0.4093 | |
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| 3.13 | 3.0 | 6768 | 3.0945 | 0.4299 | |
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| 2.9219 | 4.0 | 9024 | 2.9890 | 0.4404 | |
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| 2.8444 | 5.0 | 11280 | 2.9282 | 0.4466 | |
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| 2.7883 | 6.0 | 13536 | 2.8910 | 0.4508 | |
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| 2.7434 | 7.0 | 15792 | 2.8579 | 0.4545 | |
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| 2.7158 | 8.0 | 18048 | 2.8428 | 0.4560 | |
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| 2.6905 | 9.0 | 20304 | 2.8298 | 0.4573 | |
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| 2.6697 | 10.0 | 22560 | 2.8169 | 0.4592 | |
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| 2.6509 | 11.0 | 24816 | 2.8080 | 0.4601 | |
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| 2.6494 | 12.0 | 27072 | 2.8020 | 0.4607 | |
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| 2.6384 | 13.0 | 29328 | 2.7958 | 0.4616 | |
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| 2.6297 | 14.0 | 31584 | 2.7939 | 0.4620 | |
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| 2.612 | 15.0 | 33840 | 2.7649 | 0.4653 | |
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| 2.5667 | 16.0 | 36096 | 2.7425 | 0.4686 | |
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| 2.5177 | 17.0 | 38352 | 2.7206 | 0.4714 | |
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| 2.4607 | 18.0 | 40608 | 2.6999 | 0.4746 | |
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| 2.397 | 19.0 | 42864 | 2.6865 | 0.4773 | |
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| 2.3241 | 19.9915 | 45100 | 2.6840 | 0.4787 | |
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### Framework versions |
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- Transformers 4.48.0 |
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- Pytorch 2.5.1 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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