update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- finer-139
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bertiny-finetuned-finer
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: finer-139
+      type: finer-139
+      args: finer-139
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.5339285714285714
+    - name: Recall
+      type: recall
+      value: 0.036011080332409975
+    - name: F1
+      type: f1
+      value: 0.06747151077513258
+    - name: Accuracy
+      type: accuracy
+      value: 0.9847166143263048
+---
+
+<!-- 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. -->
+
+# bertiny-finetuned-finer
+
+This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the finer-139 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0882
+- Precision: 0.5339
+- Recall: 0.0360
+- F1: 0.0675
+- Accuracy: 0.9847
+
+## 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: 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
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0871        | 1.0   | 11255 | 0.0952          | 0.0       | 0.0    | 0.0    | 0.9843   |
+| 0.0864        | 2.0   | 22510 | 0.0895          | 0.7640    | 0.0082 | 0.0162 | 0.9844   |
+| 0.0929        | 3.0   | 33765 | 0.0882          | 0.5339    | 0.0360 | 0.0675 | 0.9847   |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.12.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1