Create README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- amazon_reviews_multi
+metrics:
+- accuracy
+model-index:
+- name: test-xlm-roberta-base-amzaon-reviews-mlm
+  results:
+  - task:
+      name: Masked Language Modeling
+      type: fill-mask
+    dataset:
+      name: amazon_reviews_multi all_languages
+      type: amazon_reviews_multi
+      args: all_languages
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.5032103794889962
+---
+
+<!-- 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. -->
+
+# test-xlm-roberta-base-amzaon-reviews-mlm
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the amazon_reviews_multi all_languages dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.1091
+- Accuracy: 0.5032
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.18.0.dev0
+- Pytorch 1.10.0
+- Datasets 1.18.3
+- Tokenizers 0.11.0