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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_anans_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_anans_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_anans_new |
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type: kanishka/counterfactual_babylm_anans_new |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.4072716245668577 |
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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_anans_new-seed_1024-1e-4 |
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This model was trained from scratch on the kanishka/counterfactual_babylm_anans_new dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4358 |
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- Accuracy: 0.4073 |
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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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| 4.0554 | 1.0 | 18595 | 4.2729 | 0.3076 | |
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| 3.5589 | 2.0 | 37190 | 3.7451 | 0.3634 | |
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| 3.3868 | 3.0 | 55785 | 3.5863 | 0.3813 | |
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| 3.2904 | 4.0 | 74380 | 3.5049 | 0.3888 | |
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| 3.2198 | 5.0 | 92975 | 3.4777 | 0.3946 | |
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| 3.1698 | 6.0 | 111570 | 3.4524 | 0.3970 | |
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| 3.1232 | 7.0 | 130165 | 3.4485 | 0.3993 | |
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| 3.0906 | 8.0 | 148760 | 3.4315 | 0.4013 | |
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| 3.0612 | 9.0 | 167355 | 3.4062 | 0.4034 | |
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| 3.0318 | 10.0 | 185950 | 3.4156 | 0.4043 | |
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| 3.0102 | 11.0 | 204545 | 3.4183 | 0.4043 | |
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| 2.9841 | 12.0 | 223140 | 3.4149 | 0.4052 | |
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| 2.9673 | 13.0 | 241735 | 3.4120 | 0.4061 | |
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| 2.9473 | 14.0 | 260330 | 3.4053 | 0.4069 | |
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| 2.9271 | 15.0 | 278925 | 3.4140 | 0.4066 | |
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| 2.9087 | 16.0 | 297520 | 3.4227 | 0.4067 | |
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| 2.8915 | 17.0 | 316115 | 3.4177 | 0.4070 | |
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| 2.8719 | 18.0 | 334710 | 3.4238 | 0.4071 | |
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| 2.8512 | 19.0 | 353305 | 3.4332 | 0.4071 | |
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| 2.8466 | 20.0 | 371900 | 3.4358 | 0.4073 | |
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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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