End of training

README.md

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+---
+base_model: airesearch/wangchanberta-base-att-spm-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: sentic-singletTextWcBerta-Fold1
+  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. -->
+
+# sentic-singletTextWcBerta-Fold1
+
+This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5203
+- Accuracy: 0.7207
+- Precision: 0.6983
+- Recall: 0.7207
+- F1 Score: 0.7008
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
+| No log        | 1.0   | 60   | 0.6400          | 0.7029   | 0.4941    | 0.7029 | 0.5803   |
+| 0.6072        | 2.0   | 120  | 0.6084          | 0.7029   | 0.4941    | 0.7029 | 0.5803   |
+| 0.6072        | 3.0   | 180  | 0.6384          | 0.7029   | 0.4941    | 0.7029 | 0.5803   |
+| 0.6201        | 4.0   | 240  | 0.5914          | 0.7029   | 0.4941    | 0.7029 | 0.5803   |
+| 0.6043        | 5.0   | 300  | 0.5983          | 0.7029   | 0.4941    | 0.7029 | 0.5803   |
+| 0.6043        | 6.0   | 360  | 0.5838          | 0.7071   | 0.6955    | 0.7071 | 0.5972   |
+| 0.5881        | 7.0   | 420  | 0.5963          | 0.6475   | 0.6661    | 0.6475 | 0.6551   |
+| 0.5881        | 8.0   | 480  | 0.5525          | 0.7155   | 0.6908    | 0.7155 | 0.6369   |
+| 0.5542        | 9.0   | 540  | 0.5241          | 0.7218   | 0.6984    | 0.7218 | 0.7000   |
+| 0.5026        | 10.0  | 600  | 0.5230          | 0.7050   | 0.6998    | 0.7050 | 0.7021   |
+| 0.5026        | 11.0  | 660  | 0.5373          | 0.7322   | 0.7106    | 0.7322 | 0.6884   |
+| 0.5048        | 12.0  | 720  | 0.5205          | 0.7123   | 0.7048    | 0.7123 | 0.7080   |
+| 0.5048        | 13.0  | 780  | 0.5207          | 0.7238   | 0.7016    | 0.7238 | 0.7034   |
+| 0.4974        | 14.0  | 840  | 0.5190          | 0.7249   | 0.7056    | 0.7249 | 0.7089   |
+| 0.4953        | 15.0  | 900  | 0.5203          | 0.7207   | 0.6983    | 0.7207 | 0.7008   |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0
+- Datasets 2.21.0
+- Tokenizers 0.19.1

model.safetensors

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 size 437958648