update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- conll2003
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: funnel-transformer-xlarge_ner_conll2003
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9565363315992617
+    - name: Recall
+      type: recall
+      value: 0.9592729720632783
+    - name: F1
+      type: f1
+      value: 0.9579026972523318
+    - name: Accuracy
+      type: accuracy
+      value: 0.9914528250457537
+---
+
+<!-- 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. -->
+
+# funnel-transformer-xlarge_ner_conll2003
+
+This model is a fine-tuned version of [funnel-transformer/xlarge](https://huggingface.co/funnel-transformer/xlarge) on the conll2003 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0436
+- Precision: 0.9565
+- Recall: 0.9593
+- F1: 0.9579
+- Accuracy: 0.9915
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1349        | 1.0   | 878  | 0.0441          | 0.9328    | 0.9438 | 0.9383 | 0.9881   |
+| 0.0308        | 2.0   | 1756 | 0.0377          | 0.9457    | 0.9561 | 0.9509 | 0.9901   |
+| 0.0144        | 3.0   | 2634 | 0.0432          | 0.9512    | 0.9578 | 0.9545 | 0.9906   |
+| 0.007         | 4.0   | 3512 | 0.0419          | 0.9551    | 0.9584 | 0.9567 | 0.9913   |
+| 0.0041        | 5.0   | 4390 | 0.0436          | 0.9565    | 0.9593 | 0.9579 | 0.9915   |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1