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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_naans_new |
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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_naans_new-seed_1024-1e-4 |
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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_naans_new |
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type: kanishka/counterfactual_babylm_naans_new |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.40723568402608223 |
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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_naans_new-seed_1024-1e-4 |
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This model was trained from scratch on the kanishka/counterfactual_babylm_naans_new dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4373 |
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- Accuracy: 0.4072 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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- seed: 1024 |
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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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| 4.0553 | 1.0 | 18595 | 4.2752 | 0.3077 | |
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| 3.5587 | 2.0 | 37190 | 3.7501 | 0.3633 | |
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| 3.3865 | 3.0 | 55785 | 3.5884 | 0.3815 | |
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| 3.2906 | 4.0 | 74380 | 3.5054 | 0.3891 | |
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| 3.2202 | 5.0 | 92975 | 3.4769 | 0.3943 | |
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| 3.1699 | 6.0 | 111570 | 3.4426 | 0.3977 | |
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| 3.1232 | 7.0 | 130165 | 3.4478 | 0.3994 | |
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| 3.091 | 8.0 | 148760 | 3.4243 | 0.4014 | |
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| 3.0613 | 9.0 | 167355 | 3.4169 | 0.4030 | |
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| 3.0322 | 10.0 | 185950 | 3.4142 | 0.4050 | |
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| 3.0107 | 11.0 | 204545 | 3.4052 | 0.4049 | |
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| 2.9844 | 12.0 | 223140 | 3.4128 | 0.4053 | |
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| 2.9671 | 13.0 | 241735 | 3.4150 | 0.4062 | |
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| 2.9477 | 14.0 | 260330 | 3.4174 | 0.4062 | |
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| 2.9272 | 15.0 | 278925 | 3.4275 | 0.4067 | |
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| 2.9088 | 16.0 | 297520 | 3.4271 | 0.4068 | |
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| 2.8915 | 17.0 | 316115 | 3.4245 | 0.4071 | |
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| 2.872 | 18.0 | 334710 | 3.4262 | 0.4070 | |
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| 2.8514 | 19.0 | 353305 | 3.4322 | 0.4073 | |
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| 2.8467 | 20.0 | 371900 | 3.4373 | 0.4072 | |
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### Framework versions |
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- Transformers 4.38.0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
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