End of training

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: wangchanberta-base-att-spm-uncased
+  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. -->
+
+# wangchanberta-base-att-spm-uncased
+
+This model was trained from scratch on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1488
+- Precision: 0.7295
+- Recall: 0.6121
+- F1: 0.6657
+- Accuracy: 0.9399
+
+## 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: 16
+- eval_batch_size: 16
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1912        | 1.0   | 1379 | 0.1583          | 0.7079    | 0.5883 | 0.6426 | 0.9355   |
+| 0.1625        | 2.0   | 2758 | 0.1488          | 0.7236    | 0.6273 | 0.6720 | 0.9399   |
+| 0.1532        | 3.0   | 4137 | 0.1488          | 0.7295    | 0.6121 | 0.6657 | 0.9399   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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