End of training

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: NLP_Capstone
+  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. -->
+
+# NLP_Capstone
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3184
+- Accuracy: 0.9131
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.4675        | 0.2   | 500   | 0.3681          | 0.8803   |
+| 0.3759        | 0.4   | 1000  | 0.5198          | 0.8721   |
+| 0.3657        | 0.6   | 1500  | 0.3482          | 0.9040   |
+| 0.3139        | 0.8   | 2000  | 0.3184          | 0.9131   |
+| 0.3442        | 1.0   | 2500  | 0.3415          | 0.9058   |
+| 0.2745        | 1.2   | 3000  | 0.3522          | 0.8745   |
+| 0.2413        | 1.41  | 3500  | 0.3306          | 0.9105   |
+| 0.2517        | 1.61  | 4000  | 0.3334          | 0.9243   |
+| 0.2499        | 1.81  | 4500  | 0.3907          | 0.9072   |
+| 0.2473        | 2.01  | 5000  | 0.3441          | 0.9229   |
+| 0.1608        | 2.21  | 5500  | 0.3697          | 0.9187   |
+| 0.173         | 2.41  | 6000  | 0.3362          | 0.9225   |
+| 0.1749        | 2.61  | 6500  | 0.3591          | 0.9237   |
+| 0.1725        | 2.81  | 7000  | 0.4014          | 0.9255   |
+| 0.1616        | 3.01  | 7500  | 0.3456          | 0.9271   |
+| 0.1047        | 3.21  | 8000  | 0.3773          | 0.9285   |
+| 0.1062        | 3.41  | 8500  | 0.3980          | 0.9217   |
+| 0.1029        | 3.61  | 9000  | 0.3808          | 0.9293   |
+| 0.1004        | 3.81  | 9500  | 0.3696          | 0.9289   |
+| 0.0822        | 4.01  | 10000 | 0.3950          | 0.9309   |
+| 0.0408        | 4.22  | 10500 | 0.4388          | 0.9285   |
+| 0.0643        | 4.42  | 11000 | 0.4204          | 0.9285   |
+| 0.0536        | 4.62  | 11500 | 0.4102          | 0.9301   |
+| 0.0508        | 4.82  | 12000 | 0.4139          | 0.9297   |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

pytorch_model.bin

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