Training completed!

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-large-uncased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: CS221-bert-large-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-large-uncased-finetuned-semeval
+
+This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3493
+- F1: 0.7668
+- Roc Auc: 0.8210
+- Accuracy: 0.4765
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 0.55          | 1.0   | 70   | 0.5378          | 0.4156 | 0.6228  | 0.1625   |
+| 0.3931        | 2.0   | 140  | 0.4018          | 0.6857 | 0.7636  | 0.3989   |
+| 0.2768        | 3.0   | 210  | 0.3776          | 0.7337 | 0.7972  | 0.4422   |
+| 0.2033        | 4.0   | 280  | 0.3493          | 0.7668 | 0.8210  | 0.4765   |
+| 0.1157        | 5.0   | 350  | 0.3954          | 0.7648 | 0.8254  | 0.4675   |
+| 0.0746        | 6.0   | 420  | 0.4089          | 0.7660 | 0.8235  | 0.4747   |
+| 0.0539        | 7.0   | 490  | 0.4444          | 0.7597 | 0.8170  | 0.4567   |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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