update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- xtreme_en_token_drift
+metrics:
+- accuracy
+- f1
+model-index:
+- name: XLM-RoBERTa-xtreme-en-token-drift
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: xtreme_en_token_drift
+      type: xtreme_en_token_drift
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.908855961405927
+    - name: F1
+      type: f1
+      value: 0.76126567683807
+---
+
+<!-- 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. -->
+
+# XLM-RoBERTa-xtreme-en-token-drift
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme_en_token_drift dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2802
+- Accuracy: 0.9089
+- F1: 0.7613
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.6398        | 1.0   | 161  | 0.3421          | 0.8973   | 0.7111 |
+| 0.3268        | 2.0   | 322  | 0.2846          | 0.9097   | 0.7611 |
+| 0.2701        | 3.0   | 483  | 0.2802          | 0.9089   | 0.7613 |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1