Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: xlnet-large-cased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: CS221-xlnet-large-cased-finetuned
+  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-xlnet-large-cased-finetuned
+
+This model is a fine-tuned version of [xlnet-large-cased](https://huggingface.co/xlnet-large-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7215
+- F1: 0.7480
+- Roc Auc: 0.8032
+- Accuracy: 0.4675
+
+## 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: 16
+- eval_batch_size: 16
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 0.5487        | 1.0   | 139  | 0.5874          | 0.1435 | 0.5     | 0.1300   |
+| 0.459         | 2.0   | 278  | 0.4370          | 0.5135 | 0.6713  | 0.3430   |
+| 0.392         | 3.0   | 417  | 0.3982          | 0.6568 | 0.7439  | 0.4116   |
+| 0.291         | 4.0   | 556  | 0.3839          | 0.7249 | 0.7924  | 0.4747   |
+| 0.2056        | 5.0   | 695  | 0.4239          | 0.7129 | 0.7791  | 0.4422   |
+| 0.1551        | 6.0   | 834  | 0.4474          | 0.7275 | 0.7883  | 0.4621   |
+| 0.0951        | 7.0   | 973  | 0.5284          | 0.7206 | 0.7797  | 0.4477   |
+| 0.0918        | 8.0   | 1112 | 0.5521          | 0.7395 | 0.7985  | 0.4458   |
+| 0.0494        | 9.0   | 1251 | 0.5826          | 0.7458 | 0.8163  | 0.4513   |
+| 0.0284        | 10.0  | 1390 | 0.6400          | 0.7337 | 0.7942  | 0.4440   |
+| 0.0188        | 11.0  | 1529 | 0.6637          | 0.7310 | 0.7913  | 0.4675   |
+| 0.0167        | 12.0  | 1668 | 0.6604          | 0.7550 | 0.8111  | 0.4675   |
+| 0.0118        | 13.0  | 1807 | 0.7297          | 0.7341 | 0.7905  | 0.4531   |
+| 0.0054        | 14.0  | 1946 | 0.7046          | 0.7542 | 0.8086  | 0.4711   |
+| 0.0043        | 15.0  | 2085 | 0.7215          | 0.7480 | 0.8032  | 0.4675   |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

model.safetensors

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