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: wcBERTaAttSpmm-ggTranslate-senticPolarEmotion-bully-f1
+  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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/herobye13579/huggingface/runs/1g8tmg7k)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/herobye13579/huggingface/runs/1g8tmg7k)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/herobye13579/huggingface/runs/1g8tmg7k)
+# wcBERTaAttSpmm-ggTranslate-senticPolarEmotion-bully-f1
+
+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: 0.5229
+- Accuracy: 0.7448
+- Precision: 0.7291
+- Recall: 0.7448
+- F1 Score: 0.7303
+
+## 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: 5e-06
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
+| 0.551         | 1.0   | 120  | 0.5535          | 0.7427   | 0.7285    | 0.7427 | 0.7311   |
+| 0.5476        | 2.0   | 240  | 0.5530          | 0.7406   | 0.7259    | 0.7406 | 0.7285   |
+| 0.5352        | 3.0   | 360  | 0.5528          | 0.7354   | 0.7261    | 0.7354 | 0.7294   |
+| 0.5482        | 4.0   | 480  | 0.5531          | 0.7312   | 0.7278    | 0.7312 | 0.7293   |
+| 0.5386        | 5.0   | 600  | 0.5547          | 0.7228   | 0.7236    | 0.7228 | 0.7232   |
+| 0.5391        | 6.0   | 720  | 0.5467          | 0.7427   | 0.7303    | 0.7427 | 0.7335   |
+| 0.5495        | 7.0   | 840  | 0.5506          | 0.7395   | 0.7305    | 0.7395 | 0.7337   |
+| 0.5305        | 8.0   | 960  | 0.5444          | 0.7427   | 0.7321    | 0.7427 | 0.7353   |
+| 0.5183        | 9.0   | 1080 | 0.5326          | 0.7448   | 0.7320    | 0.7448 | 0.7349   |
+| 0.5065        | 10.0  | 1200 | 0.5218          | 0.7479   | 0.7314    | 0.7479 | 0.7297   |
+| 0.4753        | 11.0  | 1320 | 0.5207          | 0.7469   | 0.7317    | 0.7469 | 0.7330   |
+| 0.4731        | 12.0  | 1440 | 0.5233          | 0.7458   | 0.7302    | 0.7458 | 0.7312   |
+| 0.4828        | 13.0  | 1560 | 0.5243          | 0.7458   | 0.7302    | 0.7458 | 0.7312   |
+| 0.4662        | 14.0  | 1680 | 0.5229          | 0.7458   | 0.7306    | 0.7458 | 0.7321   |
+| 0.472         | 15.0  | 1800 | 0.5229          | 0.7448   | 0.7291    | 0.7448 | 0.7303   |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

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