update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- tweet_eval
+metrics:
+- f1
+model-index:
+- name: demo_sentiment_1234567
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: tweet_eval
+      type: tweet_eval
+      args: sentiment
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.7113620044371958
+---
+
+<!-- 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. -->
+
+# demo_sentiment_1234567
+
+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: 0.6332
+- F1: 0.7114
+
+## 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: 8.62486660723695e-06
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 0
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.7592        | 1.0   | 713  | 0.6509          | 0.6834 |
+| 0.6389        | 2.0   | 1426 | 0.6318          | 0.7011 |
+| 0.5647        | 3.0   | 2139 | 0.6320          | 0.7041 |
+| 0.5391        | 4.0   | 2852 | 0.6332          | 0.7114 |
+
+
+### Framework versions
+
+- Transformers 4.12.5
+- Pytorch 1.9.1
+- Datasets 1.16.1
+- Tokenizers 0.10.3