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End of training

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README.md ADDED
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+ ---
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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-77M-MLM-finetuned-bace
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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-77M-MLM-finetuned-bace
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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: 0.0592
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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: 8
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+ - eval_batch_size: 8
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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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+ - 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 |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 152 | 0.1396 |
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+ | No log | 2.0 | 304 | 0.1761 |
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+ | No log | 3.0 | 456 | 0.1527 |
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+ | 0.2304 | 4.0 | 608 | 0.1260 |
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+ | 0.2304 | 5.0 | 760 | 0.1307 |
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+ | 0.2304 | 6.0 | 912 | 0.1256 |
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+ | 0.178 | 7.0 | 1064 | 0.1016 |
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+ | 0.178 | 8.0 | 1216 | 0.0890 |
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+ | 0.178 | 9.0 | 1368 | 0.1486 |
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+ | 0.1588 | 10.0 | 1520 | 0.1047 |
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+ | 0.1588 | 11.0 | 1672 | 0.1072 |
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+ | 0.1588 | 12.0 | 1824 | 0.1336 |
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+ | 0.1588 | 13.0 | 1976 | 0.0955 |
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+ | 0.1473 | 14.0 | 2128 | 0.0946 |
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+ | 0.1473 | 15.0 | 2280 | 0.0940 |
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+ | 0.1473 | 16.0 | 2432 | 0.0756 |
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+ | 0.1415 | 17.0 | 2584 | 0.1275 |
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+ | 0.1415 | 18.0 | 2736 | 0.1175 |
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+ | 0.1415 | 19.0 | 2888 | 0.0743 |
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+ | 0.1237 | 20.0 | 3040 | 0.0811 |
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+ | 0.1237 | 21.0 | 3192 | 0.1033 |
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+ | 0.1237 | 22.0 | 3344 | 0.0877 |
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+ | 0.1237 | 23.0 | 3496 | 0.0835 |
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+ | 0.1254 | 24.0 | 3648 | 0.1107 |
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+ | 0.1254 | 25.0 | 3800 | 0.1098 |
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+ | 0.1254 | 26.0 | 3952 | 0.1138 |
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+ | 0.1238 | 27.0 | 4104 | 0.0896 |
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+ | 0.1238 | 28.0 | 4256 | 0.0923 |
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+ | 0.1238 | 29.0 | 4408 | 0.1019 |
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+ | 0.1161 | 30.0 | 4560 | 0.1115 |
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+ | 0.1161 | 31.0 | 4712 | 0.0716 |
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+ | 0.1161 | 32.0 | 4864 | 0.1300 |
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+ | 0.114 | 33.0 | 5016 | 0.1017 |
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+ | 0.114 | 34.0 | 5168 | 0.0922 |
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+ | 0.114 | 35.0 | 5320 | 0.0458 |
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+ | 0.114 | 36.0 | 5472 | 0.1335 |
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+ | 0.1116 | 37.0 | 5624 | 0.0924 |
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+ | 0.1116 | 38.0 | 5776 | 0.0828 |
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+ | 0.1116 | 39.0 | 5928 | 0.0857 |
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+ | 0.1082 | 40.0 | 6080 | 0.0847 |
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+ | 0.1082 | 41.0 | 6232 | 0.0629 |
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+ | 0.1082 | 42.0 | 6384 | 0.0685 |
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+ | 0.11 | 43.0 | 6536 | 0.0918 |
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+ | 0.11 | 44.0 | 6688 | 0.0829 |
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+ | 0.11 | 45.0 | 6840 | 0.1118 |
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+ | 0.11 | 46.0 | 6992 | 0.0561 |
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+ | 0.1041 | 47.0 | 7144 | 0.0834 |
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+ | 0.1041 | 48.0 | 7296 | 0.0940 |
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+ | 0.1041 | 49.0 | 7448 | 0.1024 |
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+ | 0.1103 | 50.0 | 7600 | 0.0809 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ "use_cache": true,
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+ "vocab_size": 600
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+ }
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