update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- fin
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: fin1
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: fin
+      type: fin
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8315412186379928
+    - name: Recall
+      type: recall
+      value: 0.9243027888446215
+    - name: F1
+      type: f1
+      value: 0.8754716981132076
+    - name: Accuracy
+      type: accuracy
+      value: 0.985175455057234
+---
+
+<!-- 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. -->
+
+# fin1
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the fin dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0778
+- Precision: 0.8315
+- Recall: 0.9243
+- F1: 0.8755
+- Accuracy: 0.9852
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 129  | 0.0860          | 0.8535    | 0.9283 | 0.8893 | 0.9904   |
+| No log        | 2.0   | 258  | 0.1513          | 0.7993    | 0.9203 | 0.8556 | 0.9799   |
+| No log        | 3.0   | 387  | 0.0977          | 0.8221    | 0.9203 | 0.8684 | 0.9831   |
+| 0.0017        | 4.0   | 516  | 0.0783          | 0.8286    | 0.9243 | 0.8738 | 0.9848   |
+| 0.0017        | 5.0   | 645  | 0.0778          | 0.8315    | 0.9243 | 0.8755 | 0.9852   |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.0+cu116
+- Datasets 2.7.1
+- Tokenizers 0.13.2