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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_anans_new-1e-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_anans_new-1e-4 |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4007 |
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- Accuracy: 0.4074 |
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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: 42 |
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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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| 4.0511 | 1.0 | 18595 | 4.2394 | 0.3093 | |
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| 3.5633 | 2.0 | 37190 | 3.7416 | 0.3637 | |
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| 3.3921 | 3.0 | 55785 | 3.5710 | 0.3807 | |
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| 3.2853 | 4.0 | 74380 | 3.5125 | 0.3883 | |
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| 3.2219 | 5.0 | 92975 | 3.4521 | 0.3931 | |
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| 3.1716 | 6.0 | 111570 | 3.4476 | 0.3967 | |
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| 3.1281 | 7.0 | 130165 | 3.4214 | 0.3994 | |
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| 3.0951 | 8.0 | 148760 | 3.4083 | 0.4018 | |
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| 3.0631 | 9.0 | 167355 | 3.3979 | 0.4024 | |
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| 3.0407 | 10.0 | 185950 | 3.3901 | 0.4042 | |
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| 3.0103 | 11.0 | 204545 | 3.3945 | 0.4041 | |
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| 2.9879 | 12.0 | 223140 | 3.3859 | 0.4055 | |
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| 2.9716 | 13.0 | 241735 | 3.3779 | 0.4063 | |
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| 2.9449 | 14.0 | 260330 | 3.3843 | 0.4066 | |
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| 2.9277 | 15.0 | 278925 | 3.3808 | 0.4074 | |
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| 2.9087 | 16.0 | 297520 | 3.3866 | 0.4070 | |
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| 2.8913 | 17.0 | 316115 | 3.3875 | 0.4071 | |
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| 2.8771 | 18.0 | 334710 | 3.3993 | 0.4071 | |
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| 2.8633 | 19.0 | 353305 | 3.3992 | 0.4073 | |
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| 2.8505 | 20.0 | 371900 | 3.4007 | 0.4074 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.19.1 |
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