update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- lst20
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: premodel
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: lst20
+      type: lst20
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8533733110439704
+    - name: Recall
+      type: recall
+      value: 0.8653846153846154
+    - name: F1
+      type: f1
+      value: 0.8593369935367294
+    - name: Accuracy
+      type: accuracy
+      value: 0.9477067610537897
+---
+
+<!-- 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. -->
+
+# premodel
+
+This model is a fine-tuned version of [Geotrend/bert-base-th-cased](https://huggingface.co/Geotrend/bert-base-th-cased) on the lst20 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1761
+- Precision: 0.8534
+- Recall: 0.8654
+- F1: 0.8593
+- Accuracy: 0.9477
+
+## 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-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: 3.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.24.0
+- Pytorch 1.12.1+cu113
+- Datasets 2.7.0
+- Tokenizers 0.13.2