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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_211-1e-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: 0.4062615946031953 |
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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_211-1e-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: 3.4227 |
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- Accuracy: 0.4063 |
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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: 211 |
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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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| 4.0574 | 1.0 | 18595 | 4.2623 | 0.3095 | |
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| 3.5744 | 2.0 | 37190 | 3.7410 | 0.3630 | |
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| 3.3998 | 3.0 | 55785 | 3.5874 | 0.3791 | |
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| 3.2911 | 4.0 | 74380 | 3.5155 | 0.3873 | |
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| 3.2246 | 5.0 | 92975 | 3.4782 | 0.3919 | |
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| 3.1723 | 6.0 | 111570 | 3.4440 | 0.3962 | |
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| 3.1287 | 7.0 | 130165 | 3.4271 | 0.3987 | |
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| 3.0994 | 8.0 | 148760 | 3.3990 | 0.4007 | |
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| 3.0668 | 9.0 | 167355 | 3.4112 | 0.4018 | |
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| 3.0398 | 10.0 | 185950 | 3.3915 | 0.4033 | |
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| 3.0097 | 11.0 | 204545 | 3.4067 | 0.4037 | |
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| 2.9924 | 12.0 | 223140 | 3.4117 | 0.4039 | |
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| 2.9702 | 13.0 | 241735 | 3.3926 | 0.4054 | |
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| 2.9486 | 14.0 | 260330 | 3.4035 | 0.4053 | |
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| 2.9284 | 15.0 | 278925 | 3.4107 | 0.4056 | |
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| 2.9143 | 16.0 | 297520 | 3.4057 | 0.4061 | |
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| 2.8931 | 17.0 | 316115 | 3.4160 | 0.4058 | |
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| 2.8785 | 18.0 | 334710 | 3.4139 | 0.4063 | |
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| 2.8611 | 19.0 | 353305 | 3.4191 | 0.4062 | |
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| 2.8443 | 20.0 | 371900 | 3.4227 | 0.4063 | |
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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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