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README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: CS221-bert-base-uncased-finetuned-semeval
+  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. -->
+
+# CS221-bert-base-uncased-finetuned-semeval
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4411
+- F1: 0.7582
+- Roc Auc: 0.8177
+- Accuracy: 0.4513
+
+## 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 adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 0.5838        | 1.0   | 70   | 0.5717          | 0.4152 | 0.6139  | 0.1426   |
+| 0.4291        | 2.0   | 140  | 0.4290          | 0.6732 | 0.7555  | 0.3430   |
+| 0.3488        | 3.0   | 210  | 0.3820          | 0.7272 | 0.7954  | 0.3899   |
+| 0.2618        | 4.0   | 280  | 0.3659          | 0.7402 | 0.8037  | 0.4278   |
+| 0.1956        | 5.0   | 350  | 0.3755          | 0.7442 | 0.8083  | 0.4260   |
+| 0.1611        | 6.0   | 420  | 0.3768          | 0.7491 | 0.8103  | 0.4477   |
+| 0.1204        | 7.0   | 490  | 0.4027          | 0.7389 | 0.8019  | 0.4531   |
+| 0.0847        | 8.0   | 560  | 0.4063          | 0.7525 | 0.8149  | 0.4513   |
+| 0.0743        | 9.0   | 630  | 0.4221          | 0.7464 | 0.8077  | 0.4477   |
+| 0.0552        | 10.0  | 700  | 0.4359          | 0.7462 | 0.8074  | 0.4531   |
+| 0.0475        | 11.0  | 770  | 0.4411          | 0.7582 | 0.8177  | 0.4513   |
+| 0.0315        | 12.0  | 840  | 0.4549          | 0.7487 | 0.8097  | 0.4495   |
+| 0.0287        | 13.0  | 910  | 0.4645          | 0.75   | 0.8108  | 0.4531   |
+| 0.0272        | 14.0  | 980  | 0.4682          | 0.7555 | 0.8158  | 0.4531   |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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