update model card README.md

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- swag
+metrics:
+- accuracy
+model-index:
+- name: distilbert-swag
+  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. -->
+
+# distilbert-swag
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the swag dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9079
+- Accuracy: 0.7105
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.9186        | 1.0   | 2298 | 0.7658          | 0.6950   |
+| 0.5843        | 2.0   | 4597 | 0.7453          | 0.7059   |
+| 0.3548        | 3.0   | 6894 | 0.9079          | 0.7105   |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1
+- Datasets 2.13.1
+- Tokenizers 0.13.3