update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- wikiann
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: funnel-transformer-xlarge_ner_wikiann
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: wikiann
+      type: wikiann
+      args: en
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8522084990579862
+    - name: Recall
+      type: recall
+      value: 0.8633535981903011
+    - name: F1
+      type: f1
+      value: 0.8577448467184043
+    - name: Accuracy
+      type: accuracy
+      value: 0.935805105791199
+---
+
+<!-- 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_wikiann
+
+This model is a fine-tuned version of [funnel-transformer/xlarge](https://huggingface.co/funnel-transformer/xlarge) on the wikiann dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4023
+- Precision: 0.8522
+- Recall: 0.8634
+- F1: 0.8577
+- Accuracy: 0.9358
+
+## 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: 1e-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: cosine
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.3193        | 1.0   | 5000  | 0.3116          | 0.8239    | 0.8296 | 0.8267 | 0.9260   |
+| 0.2836        | 2.0   | 10000 | 0.2846          | 0.8446    | 0.8498 | 0.8472 | 0.9325   |
+| 0.2237        | 3.0   | 15000 | 0.3258          | 0.8427    | 0.8542 | 0.8484 | 0.9332   |
+| 0.1303        | 4.0   | 20000 | 0.3801          | 0.8531    | 0.8634 | 0.8582 | 0.9362   |
+| 0.0867        | 5.0   | 25000 | 0.4023          | 0.8522    | 0.8634 | 0.8577 | 0.9358   |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1