Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/deberta-v3-base
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: CS221-deberta-v3-base-finetuned-augmentation
+  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-deberta-v3-base-finetuned-augmentation
+
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2285
+- F1: 0.9258
+- Roc Auc: 0.9451
+- Accuracy: 0.8548
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 0.4444        | 1.0   | 180  | 0.4238          | 0.5147 | 0.6834  | 0.3621   |
+| 0.3212        | 2.0   | 360  | 0.3233          | 0.7223 | 0.7933  | 0.5024   |
+| 0.2397        | 3.0   | 540  | 0.2473          | 0.8341 | 0.8798  | 0.6442   |
+| 0.1506        | 4.0   | 720  | 0.2095          | 0.8683 | 0.9076  | 0.7262   |
+| 0.0987        | 5.0   | 900  | 0.2038          | 0.8838 | 0.9122  | 0.7498   |
+| 0.0659        | 6.0   | 1080 | 0.1869          | 0.9068 | 0.9311  | 0.8151   |
+| 0.0432        | 7.0   | 1260 | 0.2043          | 0.9027 | 0.9253  | 0.8096   |
+| 0.029         | 8.0   | 1440 | 0.1907          | 0.9135 | 0.9337  | 0.8270   |
+| 0.02          | 9.0   | 1620 | 0.1930          | 0.9240 | 0.9423  | 0.8520   |
+| 0.0128        | 10.0  | 1800 | 0.2234          | 0.9180 | 0.9402  | 0.8381   |
+| 0.0115        | 11.0  | 1980 | 0.2132          | 0.9185 | 0.9395  | 0.8409   |
+| 0.01          | 12.0  | 2160 | 0.2166          | 0.9249 | 0.9440  | 0.8520   |
+| 0.0055        | 13.0  | 2340 | 0.2182          | 0.9267 | 0.9438  | 0.8568   |
+| 0.0057        | 14.0  | 2520 | 0.2263          | 0.9245 | 0.9445  | 0.8562   |
+| 0.0041        | 15.0  | 2700 | 0.2246          | 0.9254 | 0.9464  | 0.8555   |
+| 0.0043        | 16.0  | 2880 | 0.2285          | 0.9258 | 0.9451  | 0.8548   |
+
+
+### 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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