update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- xtreme
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-multilingual-finetuned-xtreme-tamil-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: xtreme
+      type: xtreme
+      config: PAN-X.ta
+      split: train
+      args: PAN-X.ta
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.746268656716418
+    - name: Recall
+      type: recall
+      value: 0.819672131147541
+    - name: F1
+      type: f1
+      value: 0.7812500000000001
+    - name: Accuracy
+      type: accuracy
+      value: 0.9236328484625299
+---
+
+<!-- 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-multilingual-finetuned-xtreme-tamil-ner
+
+This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the xtreme dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2338
+- Precision: 0.7463
+- Recall: 0.8197
+- F1: 0.7813
+- Accuracy: 0.9236
+
+## 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 | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.3899        | 1.0   | 469  | 0.2517          | 0.6893    | 0.7893 | 0.7360 | 0.9143   |
+| 0.2093        | 2.0   | 938  | 0.2338          | 0.7463    | 0.8197 | 0.7813 | 0.9236   |
+
+
+### Framework versions
+
+- Transformers 4.22.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1