---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-NER-ind
  results: []
---

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![image/png](https://cdn-uploads.huggingface.co/production/uploads/62c7a3411e080b837465edc7/TilhXzvXVq2FZv1DYot_f.png)

# xlm-roberta-base-NER-ind

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1404
- F1: 0.8130

## Model description

Model is trained specifically for indian context, we used sentence-piece tokenizer to train the model, so use the sentences with proper delimeter like(. , ?) and appropiate capitalization of words.

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| No log        | 1.0   | 2509  | 0.1427          | 0.7972 |
| No log        | 2.0   | 5019  | 0.1366          | 0.8101 |
| 0.1384        | 3.0   | 7529  | 0.1366          | 0.8139 |
| 0.1384        | 4.0   | 10036 | 0.1404          | 0.8130 |


### Framework versions

- Transformers 4.27.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3