---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-multilingual-cased-indic_glue
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-multilingual-cased-indic_glue

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2873
- Precision: 0.8099
- Recall: 0.8251
- F1: 0.8175
- Accuracy: 0.9114

## 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: 32
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6012        | 0.31  | 200  | 0.3849          | 0.7566    | 0.7108 | 0.7330 | 0.8722   |
| 0.377         | 0.62  | 400  | 0.3365          | 0.7696    | 0.7837 | 0.7766 | 0.8886   |
| 0.3205        | 0.94  | 600  | 0.3093          | 0.7875    | 0.7864 | 0.7869 | 0.8961   |
| 0.2517        | 1.25  | 800  | 0.3050          | 0.8039    | 0.8131 | 0.8085 | 0.9050   |
| 0.2034        | 1.56  | 1000 | 0.2950          | 0.8129    | 0.8130 | 0.8130 | 0.9098   |
| 0.1968        | 1.88  | 1200 | 0.2873          | 0.8099    | 0.8251 | 0.8175 | 0.9114   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3