update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: medium-base-News_About_Gold
+  results: []
+---
+
+<!-- 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. -->
+
+# medium-base-News_About_Gold
+
+This model is a fine-tuned version of [funnel-transformer/medium-base](https://huggingface.co/funnel-transformer/medium-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2838
+- Accuracy: 0.9172
+- Weighted f1: 0.9170
+- Micro f1: 0.9172
+- Macro f1: 0.8854
+- Weighted recall: 0.9172
+- Micro recall: 0.9172
+- Macro recall: 0.8859
+- Weighted precision: 0.9171
+- Micro precision: 0.9172
+- Macro precision: 0.8853
+
+## 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: 64
+- eval_batch_size: 64
+- 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 | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
+| 0.7426        | 1.0   | 133  | 0.3820          | 0.8803   | 0.8636      | 0.8803   | 0.6690   | 0.8803          | 0.8803       | 0.6809       | 0.8862             | 0.8803          | 0.8992          |
+| 0.332         | 2.0   | 266  | 0.3083          | 0.9007   | 0.8987      | 0.9007   | 0.8525   | 0.9007          | 0.9007       | 0.8402       | 0.9015             | 0.9007          | 0.8705          |
+| 0.2381        | 3.0   | 399  | 0.2870          | 0.9106   | 0.9097      | 0.9106   | 0.8686   | 0.9106          | 0.9106       | 0.8539       | 0.9096             | 0.9106          | 0.8862          |
+| 0.1911        | 4.0   | 532  | 0.2797          | 0.9163   | 0.9158      | 0.9163   | 0.8843   | 0.9163          | 0.9163       | 0.8819       | 0.9159             | 0.9163          | 0.8873          |
+| 0.1584        | 5.0   | 665  | 0.2838          | 0.9172   | 0.9170      | 0.9172   | 0.8854   | 0.9172          | 0.9172       | 0.8859       | 0.9171             | 0.9172          | 0.8853          |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0
+- Datasets 2.11.0
+- Tokenizers 0.13.3