update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- tweet_eval
+metrics:
+- accuracy
+model-index:
+- name: AIE-Assessment
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: tweet_eval
+      type: tweet_eval
+      config: emotion
+      split: test
+      args: emotion
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7973258268824771
+---
+
+<!-- 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. -->
+
+# AIE-Assessment
+
+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: 0.5657
+- Accuracy: 0.7973
+
+## 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: 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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 204  | 0.6409          | 0.7875   |
+| No log        | 2.0   | 408  | 0.5657          | 0.7973   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.11.0