update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- silicone
+metrics:
+- accuracy
+model-index:
+- name: twitter-roberta-base-sentiment
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: silicone
+      type: silicone
+      config: swda
+      split: test
+      args: swda
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7383935151068534
+---
+
+<!-- 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. -->
+
+# twitter-roberta-base-sentiment
+
+This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on the silicone dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8422
+- Accuracy: 0.7384
+- Micro-precision: 0.7384
+- Micro-recall: 0.7384
+- Micro-f1: 0.7384
+- Macro-precision: 0.4914
+- Macro-recall: 0.4392
+- Macro-f1: 0.4373
+- Weighted-precision: 0.7095
+- Weighted-recall: 0.7384
+- Weighted-f1: 0.7133
+
+## 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: 32
+- eval_batch_size: 32
+- 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 | Micro-precision | Micro-recall | Micro-f1 | Macro-precision | Macro-recall | Macro-f1 | Weighted-precision | Weighted-recall | Weighted-f1 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
+| 0.8271        | 1.0   | 5960  | 0.8467          | 0.7410   | 0.7410          | 0.7410       | 0.7410   | 0.4798          | 0.4163       | 0.4203   | 0.7098             | 0.7410          | 0.7165      |
+| 0.7774        | 2.0   | 11920 | 0.8422          | 0.7384   | 0.7384          | 0.7384       | 0.7384   | 0.4914          | 0.4392       | 0.4373   | 0.7095             | 0.7384          | 0.7133      |
+
+
+### Framework versions
+
+- Transformers 4.26.0
+- Pytorch 1.13.1+cu116
+- Datasets 2.9.0
+- Tokenizers 0.13.2