---
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