Training complete

README.md

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+---
+base_model: YituTech/conv-bert-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: conv-bert-base
+  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. -->
+
+# conv-bert-base
+
+This model is a fine-tuned version of [YituTech/conv-bert-base](https://huggingface.co/YituTech/conv-bert-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2024
+- Precision: 0.7686
+- Recall: 0.8278
+- F1: 0.7971
+- Accuracy: 0.9376
+
+## 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: 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2235        | 1.0   | 2078 | 0.2225          | 0.7307    | 0.7996 | 0.7636 | 0.9301   |
+| 0.1814        | 2.0   | 4156 | 0.1946          | 0.7539    | 0.8257 | 0.7881 | 0.9363   |
+| 0.1469        | 3.0   | 6234 | 0.2024          | 0.7686    | 0.8278 | 0.7971 | 0.9376   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1