---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: muril-base-cased-finetuned-code-mixed-DS
  results: []
---

<!-- 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. -->

# muril-base-cased-finetuned-code-mixed-DS

This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2296
- Accuracy: 0.7002
- Precision: 0.6399
- Recall: 0.6265
- F1: 0.6273

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 43
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 35

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0588        | 1.98  | 248  | 0.9827          | 0.5815   | 0.3985    | 0.5400 | 0.4263 |
| 0.9378        | 3.97  | 496  | 0.9008          | 0.5976   | 0.3943    | 0.5477 | 0.4338 |
| 0.8398        | 5.95  | 744  | 0.8357          | 0.5956   | 0.4079    | 0.5579 | 0.4378 |
| 0.7621        | 7.94  | 992  | 0.8357          | 0.6157   | 0.5545    | 0.5605 | 0.4716 |
| 0.6944        | 9.92  | 1240 | 0.8643          | 0.6499   | 0.5919    | 0.5874 | 0.5452 |
| 0.632         | 11.9  | 1488 | 0.8697          | 0.6781   | 0.6075    | 0.6083 | 0.5959 |
| 0.5632        | 13.89 | 1736 | 0.9161          | 0.6962   | 0.6136    | 0.6001 | 0.6047 |
| 0.4945        | 15.87 | 1984 | 0.8818          | 0.6861   | 0.6081    | 0.6109 | 0.6093 |
| 0.4221        | 17.86 | 2232 | 0.9333          | 0.7042   | 0.6350    | 0.6350 | 0.6348 |
| 0.3725        | 19.84 | 2480 | 0.9893          | 0.6982   | 0.6279    | 0.6168 | 0.6193 |
| 0.324         | 21.82 | 2728 | 0.9935          | 0.6922   | 0.6298    | 0.6169 | 0.6163 |
| 0.2864        | 23.81 | 2976 | 1.0814          | 0.7042   | 0.6400    | 0.6233 | 0.6243 |
| 0.2577        | 25.79 | 3224 | 1.1441          | 0.7082   | 0.6455    | 0.6302 | 0.6337 |
| 0.2336        | 27.78 | 3472 | 1.1693          | 0.6982   | 0.6405    | 0.6242 | 0.6254 |
| 0.2155        | 29.76 | 3720 | 1.1397          | 0.7042   | 0.6456    | 0.6405 | 0.6396 |
| 0.2086        | 31.74 | 3968 | 1.1803          | 0.7002   | 0.6408    | 0.6302 | 0.6278 |
| 0.1923        | 33.73 | 4216 | 1.2296          | 0.7002   | 0.6399    | 0.6265 | 0.6273 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1