update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- xnli
+metrics:
+- accuracy
+model-index:
+- name: bert-xnli-de-classifier
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: xnli
+      type: xnli
+      config: de
+      split: validation
+      args: de
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7807228915662651
+---
+
+<!-- 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. -->
+
+# bert-xnli-de-classifier
+
+This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on the xnli dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5897
+- Accuracy: 0.7807
+
+## 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: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.554         | 1.0   | 6136  | 0.5783          | 0.7675   |
+| 0.4946        | 2.0   | 12272 | 0.5471          | 0.7892   |
+| 0.3416        | 3.0   | 18408 | 0.5897          | 0.7807   |
+
+
+### Framework versions
+
+- Transformers 4.27.3
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
+- Tokenizers 0.13.2