Training updated, WD = 0.01

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert-base-cased-finetuned-AddedTokens-HMGCR-IC50s-V1
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bert-base-cased-finetuned-AddedTokens-HMGCR-IC50s-V1
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7167
+- Accuracy: 0.7857
+- F1: 0.7887
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.9314        | 1.0   | 25   | 0.8466          | 0.7071   | 0.6371 |
+| 0.7535        | 2.0   | 50   | 0.7025          | 0.7357   | 0.6634 |
+| 0.6292        | 3.0   | 75   | 0.6237          | 0.7714   | 0.6956 |
+| 0.5464        | 4.0   | 100  | 0.6162          | 0.7571   | 0.7137 |
+| 0.5068        | 5.0   | 125  | 0.5730          | 0.7857   | 0.7185 |
+| 0.4516        | 6.0   | 150  | 0.5872          | 0.7643   | 0.7312 |
+| 0.3971        | 7.0   | 175  | 0.6004          | 0.7643   | 0.7578 |
+| 0.3768        | 8.0   | 200  | 0.6253          | 0.7714   | 0.7739 |
+| 0.3353        | 9.0   | 225  | 0.6280          | 0.7786   | 0.7522 |
+| 0.3439        | 10.0  | 250  | 0.6299          | 0.7714   | 0.7613 |
+| 0.3087        | 11.0  | 275  | 0.6569          | 0.7786   | 0.7719 |
+| 0.2979        | 12.0  | 300  | 0.6308          | 0.7714   | 0.7753 |
+| 0.2561        | 13.0  | 325  | 0.6596          | 0.7786   | 0.7786 |
+| 0.2703        | 14.0  | 350  | 0.6646          | 0.7786   | 0.7808 |
+| 0.2504        | 15.0  | 375  | 0.7125          | 0.7857   | 0.7913 |
+| 0.2397        | 16.0  | 400  | 0.6893          | 0.7786   | 0.7770 |
+| 0.2152        | 17.0  | 425  | 0.7278          | 0.7929   | 0.7931 |
+| 0.2066        | 18.0  | 450  | 0.6947          | 0.7857   | 0.7895 |
+| 0.2133        | 19.0  | 475  | 0.7202          | 0.7714   | 0.7756 |
+| 0.202         | 20.0  | 500  | 0.7167          | 0.7857   | 0.7887 |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.3.0
+- Tokenizers 0.21.0

model.safetensors

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