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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-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-clean-spacy-32k-earlystop_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-clean-spacy |
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type: kanishka/babylm2-clean-spacy |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.43054403912594785 |
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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-clean-spacy-32k-earlystop_seed-42_1e-3 |
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This model was trained from scratch on the kanishka/babylm2-clean-spacy dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.9103 |
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- Accuracy: 0.4305 |
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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: 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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| 5.9107 | 0.9995 | 1942 | 3.9887 | 0.3269 | |
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| 3.7896 | 1.9996 | 3885 | 3.5236 | 0.3657 | |
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| 3.3813 | 2.9997 | 5828 | 3.3040 | 0.3859 | |
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| 3.174 | 3.9997 | 7771 | 3.1921 | 0.3962 | |
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| 3.0533 | 4.9998 | 9714 | 3.1266 | 0.4026 | |
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| 2.9768 | 5.9999 | 11657 | 3.0838 | 0.4071 | |
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| 2.9232 | 6.9999 | 13600 | 3.0550 | 0.4101 | |
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| 2.8863 | 8.0 | 15543 | 3.0363 | 0.4122 | |
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| 2.8563 | 8.9995 | 17485 | 3.0208 | 0.4139 | |
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| 2.8356 | 9.9996 | 19428 | 3.0117 | 0.4151 | |
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| 2.816 | 10.9997 | 21371 | 3.0030 | 0.4162 | |
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| 2.8069 | 11.9997 | 23314 | 2.9951 | 0.4170 | |
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| 2.7941 | 12.9998 | 25257 | 2.9923 | 0.4175 | |
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| 2.7889 | 13.9999 | 27200 | 2.9888 | 0.4182 | |
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| 2.7802 | 14.9999 | 29143 | 2.9839 | 0.4186 | |
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| 2.7802 | 16.0 | 31086 | 2.9821 | 0.4190 | |
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| 2.7665 | 16.9995 | 33028 | 2.9626 | 0.4212 | |
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| 2.6908 | 17.9996 | 34971 | 2.9378 | 0.4247 | |
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| 2.6058 | 18.9997 | 36914 | 2.9145 | 0.4284 | |
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| 2.505 | 19.9910 | 38840 | 2.9103 | 0.4305 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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