update model card README.md

README.md

@@ -4,36 +4,9 @@ tags:
 - generated_from_trainer
 datasets:
 - wnut_17
-metrics:
-- precision
-- recall
-- f1
-- accuracy
 model-index:
 - name: token_classification_wnut
-  results:
-  - task:
-      name: Token Classification
-      type: token-classification
-    dataset:
-      name: wnut_17
-      type: wnut_17
-      config: wnut_17
-      split: train
-      args: wnut_17
-    metrics:
-    - name: Precision
-      type: precision
-      value: 0.5846994535519126
-    - name: Recall
-      type: recall
-      value: 0.39666357738646896
-    - name: F1
-      type: f1
-      value: 0.47266703478741023
-    - name: Accuracy
-      type: accuracy
-      value: 0.947714933093925
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -41,13 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # token_classification_wnut
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wnut_17 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2932
-- Precision: 0.5847
-- Recall: 0.3967
-- F1: 0.4727
-- Accuracy: 0.9477
+This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the wnut_17 dataset.
 
 ## Model description
 
@@ -66,20 +33,19 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- learning_rate: 4e-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: linear
-- num_epochs: 2
+- num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 107  | 0.2419          | 0.5242    | 0.4319 | 0.4736 | 0.9469   |
-| No log        | 2.0   | 214  | 0.2932          | 0.5847    | 0.3967 | 0.4727 | 0.9477   |
+| No log        | 1.0   | 213  | 0.3717          | 0.6279    | 0.3707 | 0.4662 | 0.9481   |
 
 
 ### Framework versions