End of training

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: CN_RoBERTa_Dig
+  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. -->
+
+# CN_RoBERTa_Dig
+
+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: 0.0055
+- F1: {'f1': 0.9988009592326139}
+- Accuracy: {'accuracy': 0.9988}
+
+## 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: 1e-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: 1
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | F1                         | Accuracy             |
+|:-------------:|:-----:|:-----:|:---------------:|:--------------------------:|:--------------------:|
+| 0.4018        | 0.09  | 1000  | 0.3457          | {'f1': 0.6695906432748538} | {'accuracy': 0.7514} |
+| 0.3392        | 0.18  | 2000  | 0.2601          | {'f1': 0.9148995796356842} | {'accuracy': 0.9089} |
+| 0.2443        | 0.27  | 3000  | 0.1276          | {'f1': 0.9713375796178344} | {'accuracy': 0.9712} |
+| 0.1399        | 0.36  | 4000  | 0.0616          | {'f1': 0.9867973594718943} | {'accuracy': 0.9868} |
+| 0.0926        | 0.44  | 5000  | 0.0280          | {'f1': 0.9927341494973624} | {'accuracy': 0.9927} |
+| 0.0835        | 0.53  | 6000  | 0.0260          | {'f1': 0.9942196531791908} | {'accuracy': 0.9942} |
+| 0.0617        | 0.62  | 7000  | 0.0129          | {'f1': 0.9969981989193516} | {'accuracy': 0.997}  |
+| 0.0459        | 0.71  | 8000  | 0.0097          | {'f1': 0.9977029861180465} | {'accuracy': 0.9977} |
+| 0.0363        | 0.8   | 9000  | 0.0111          | {'f1': 0.9976047904191618} | {'accuracy': 0.9976} |
+| 0.0421        | 0.89  | 10000 | 0.0078          | {'f1': 0.9980035935316429} | {'accuracy': 0.998}  |
+| 0.0317        | 0.98  | 11000 | 0.0055          | {'f1': 0.9988009592326139} | {'accuracy': 0.9988} |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

runs/Nov17_22-21-47_e8be26fc8ebd/events.out.tfevents.1700259714.e8be26fc8ebd.507.1

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