update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- tweet_eval
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert-base-uncased-finetuned-tweet_eval-offensive
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: tweet_eval
+      type: tweet_eval
+      args: offensive
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8089123867069486
+    - name: F1
+      type: f1
+      value: 0.8060281168230459
+---
+
+<!-- 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. -->
+
+# distilbert-base-uncased-finetuned-tweet_eval-offensive
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4185
+- Accuracy: 0.8089
+- F1: 0.8060
+
+## 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: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 1.0   | 187  | 0.4259          | 0.8059   | 0.7975 |
+| 0.46          | 2.0   | 374  | 0.4185          | 0.8089   | 0.8060 |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.9.1
+- Datasets 2.1.0
+- Tokenizers 0.12.1