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chemberta-clintox-tunned-1

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roberta
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: DeepChem/ChemBERTa-77M-MLM
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: chemberta-clintox-tunned-1
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+ results: []
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+ ---
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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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+
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+ # chemberta-clintox-tunned-1
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+
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+ This model is a fine-tuned version of [DeepChem/ChemBERTa-77M-MLM](https://huggingface.co/DeepChem/ChemBERTa-77M-MLM) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2171
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+ - Auc: 0.7873
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Auc |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.4703 | 1.0 | 74 | 0.4073 | 0.4833 |
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+ | 0.227 | 2.0 | 148 | 0.2215 | 0.5420 |
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+ | 0.2968 | 3.0 | 222 | 0.1996 | 0.6373 |
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+ | 0.2641 | 4.0 | 296 | 0.1979 | 0.6768 |
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+ | 0.2579 | 5.0 | 370 | 0.1940 | 0.6626 |
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+ | 0.1752 | 6.0 | 444 | 0.1894 | 0.6748 |
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+ | 0.339 | 7.0 | 518 | 0.1903 | 0.6879 |
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+ | 0.1903 | 8.0 | 592 | 0.1897 | 0.7082 |
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+ | 0.2189 | 9.0 | 666 | 0.1874 | 0.7285 |
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+ | 0.2125 | 10.0 | 740 | 0.1840 | 0.7568 |
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+ | 0.226 | 11.0 | 814 | 0.1851 | 0.7781 |
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+ | 0.2072 | 12.0 | 888 | 0.1916 | 0.7801 |
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+ | 0.236 | 13.0 | 962 | 0.1900 | 0.7923 |
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+ | 0.188 | 14.0 | 1036 | 0.1897 | 0.7984 |
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+ | 0.2019 | 15.0 | 1110 | 0.1807 | 0.8055 |
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+ | 0.217 | 16.0 | 1184 | 0.1956 | 0.8105 |
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+ | 0.1673 | 17.0 | 1258 | 0.1989 | 0.8176 |
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+ | 0.2159 | 18.0 | 1332 | 0.1784 | 0.8298 |
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+ | 0.1879 | 19.0 | 1406 | 0.1943 | 0.8237 |
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+ | 0.1627 | 20.0 | 1480 | 0.1993 | 0.8227 |
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+ | 0.1617 | 21.0 | 1554 | 0.1808 | 0.8369 |
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+ | 0.1151 | 22.0 | 1628 | 0.1700 | 0.8440 |
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+ | 0.1272 | 23.0 | 1702 | 0.1960 | 0.8430 |
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+ | 0.1553 | 24.0 | 1776 | 0.1914 | 0.8389 |
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+ | 0.1288 | 25.0 | 1850 | 0.2069 | 0.8328 |
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+ | 0.1726 | 26.0 | 1924 | 0.1907 | 0.8419 |
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+ | 0.1407 | 27.0 | 1998 | 0.2305 | 0.8298 |
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+ | 0.1589 | 28.0 | 2072 | 0.2238 | 0.8328 |
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+ | 0.0726 | 29.0 | 2146 | 0.2218 | 0.8369 |
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+ | 0.1347 | 30.0 | 2220 | 0.2073 | 0.8399 |
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+ | 0.1131 | 31.0 | 2294 | 0.2275 | 0.8399 |
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+ | 0.1416 | 32.0 | 2368 | 0.2386 | 0.8389 |
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+ | 0.1882 | 33.0 | 2442 | 0.2342 | 0.8379 |
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+ | 0.2006 | 34.0 | 2516 | 0.2283 | 0.8359 |
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+ | 0.1176 | 35.0 | 2590 | 0.2544 | 0.8308 |
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+ | 0.0942 | 36.0 | 2664 | 0.2247 | 0.8369 |
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+ | 0.1113 | 37.0 | 2738 | 0.2486 | 0.8379 |
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+ | 0.119 | 38.0 | 2812 | 0.2303 | 0.8409 |
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+ | 0.0865 | 39.0 | 2886 | 0.2623 | 0.8379 |
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+ | 0.1399 | 40.0 | 2960 | 0.2463 | 0.8379 |
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+ | 0.1771 | 41.0 | 3034 | 0.2440 | 0.8399 |
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+ | 0.1106 | 42.0 | 3108 | 0.2550 | 0.8369 |
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+ | 0.128 | 43.0 | 3182 | 0.2553 | 0.8359 |
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+ | 0.1155 | 44.0 | 3256 | 0.2500 | 0.8409 |
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+ | 0.1184 | 45.0 | 3330 | 0.2531 | 0.8409 |
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+ | 0.1274 | 46.0 | 3404 | 0.2517 | 0.8409 |
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+ | 0.0638 | 47.0 | 3478 | 0.2561 | 0.8409 |
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+ | 0.1279 | 48.0 | 3552 | 0.2554 | 0.8409 |
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+ | 0.1023 | 49.0 | 3626 | 0.2589 | 0.8399 |
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+ | 0.1278 | 50.0 | 3700 | 0.2594 | 0.8399 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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