update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- udpos28
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: udpos28-sm-all-POS
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: udpos28
+      type: udpos28
+      args: en
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9586517032792105
+    - name: Recall
+      type: recall
+      value: 0.9588997472284696
+    - name: F1
+      type: f1
+      value: 0.9587757092110369
+    - name: Accuracy
+      type: accuracy
+      value: 0.964820639556654
+---
+
+<!-- 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. -->
+
+# udpos28-sm-all-POS
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the udpos28 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1479
+- Precision: 0.9587
+- Recall: 0.9589
+- F1: 0.9588
+- Accuracy: 0.9648
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1261        | 1.0   | 4978  | 0.1358          | 0.9513    | 0.9510 | 0.9512 | 0.9581   |
+| 0.0788        | 2.0   | 9956  | 0.1326          | 0.9578    | 0.9578 | 0.9578 | 0.9642   |
+| 0.0424        | 3.0   | 14934 | 0.1479          | 0.9587    | 0.9589 | 0.9588 | 0.9648   |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.10.2+cu102
+- Datasets 2.2.2
+- Tokenizers 0.12.1