Porameht/wangchanberta-thainer-corpus-v2-2-10

README.md

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+---
+library_name: transformers
+base_model: airesearch/wangchanberta-base-att-spm-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: wangchanberta-thainer-corpus-v2-2-10
+  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-thainer-corpus-v2-2-10
+
+This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1053
+- Precision: 0.8300
+- Recall: 0.8870
+- F1: 0.8575
+- Accuracy: 0.9717
+
+## 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: 16
+- eval_batch_size: 16
+- 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: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 274  | 0.1790          | 0.6867    | 0.7908 | 0.7351 | 0.9484   |
+| 0.2681        | 2.0   | 548  | 0.1331          | 0.7788    | 0.8463 | 0.8111 | 0.9650   |
+| 0.2681        | 3.0   | 822  | 0.1135          | 0.8082    | 0.8766 | 0.8410 | 0.9692   |
+| 0.0829        | 4.0   | 1096 | 0.1053          | 0.8300    | 0.8870 | 0.8575 | 0.9717   |
+| 0.0829        | 5.0   | 1370 | 0.1136          | 0.8175    | 0.8868 | 0.8507 | 0.9704   |
+| 0.0512        | 6.0   | 1644 | 0.1135          | 0.8408    | 0.8836 | 0.8616 | 0.9723   |
+| 0.0512        | 7.0   | 1918 | 0.1162          | 0.8429    | 0.8894 | 0.8656 | 0.9725   |
+| 0.037         | 8.0   | 2192 | 0.1205          | 0.8475    | 0.8916 | 0.8690 | 0.9730   |
+| 0.037         | 9.0   | 2466 | 0.1237          | 0.8490    | 0.8942 | 0.8710 | 0.9732   |
+| 0.0275        | 10.0  | 2740 | 0.1222          | 0.8480    | 0.8934 | 0.8701 | 0.9733   |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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