update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: mega-base-wikitext-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. -->
+
+# mega-base-wikitext-News_About_Gold
+
+This model is a fine-tuned version of [mnaylor/mega-base-wikitext](https://huggingface.co/mnaylor/mega-base-wikitext) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0031
+- Accuracy: 0.5014
+- Weighted f1: 0.4023
+- Micro f1: 0.5014
+- Macro f1: 0.3282
+- Weighted recall: 0.5014
+- Micro recall: 0.5014
+- Macro recall: 0.3835
+- Weighted precision: 0.5783
+- Micro precision: 0.5014
+- Macro precision: 0.4548
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
+| 1.2255        | 1.0   | 133  | 1.1365          | 0.4134   | 0.2437      | 0.4134   | 0.1487   | 0.4134          | 0.4134       | 0.2507       | 0.2652             | 0.4134          | 0.2285          |
+| 1.1337        | 2.0   | 266  | 1.0851          | 0.4532   | 0.3257      | 0.4532   | 0.2539   | 0.4532          | 0.4532       | 0.3161       | 0.3015             | 0.4532          | 0.2705          |
+| 1.0847        | 3.0   | 399  | 1.0384          | 0.4759   | 0.3591      | 0.4759   | 0.2915   | 0.4759          | 0.4759       | 0.3520       | 0.6352             | 0.4759          | 0.4942          |
+| 1.05          | 4.0   | 532  | 1.0112          | 0.4962   | 0.3917      | 0.4962   | 0.3206   | 0.4962          | 0.4962       | 0.3783       | 0.5846             | 0.4962          | 0.4596          |
+| 1.0309        | 5.0   | 665  | 1.0031          | 0.5014   | 0.4023      | 0.5014   | 0.3282   | 0.5014          | 0.5014       | 0.3835       | 0.5783             | 0.5014          | 0.4548          |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0
+- Datasets 2.11.0
+- Tokenizers 0.13.3