---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: lexical_classifier_bangla_assamese_v2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# lexical_classifier_bangla_assamese_v2

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on [https://huggingface.co/datasets/anrikus/lexical_diff_bangla_assamese_v2].
It achieves the following results on the evaluation set:
- Loss: 1.1317
- Accuracy: 0.7033
- Precision: 0.7480
- Recall: 0.6133
- F1: 0.6740

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1501        | 1.0   | 35   | 1.0773          | 0.7286   | 0.7302    | 0.6866 | 0.7077 |
| 0.1789        | 2.0   | 70   | 0.8471          | 0.7714   | 0.7869    | 0.7164 | 0.7500 |
| 0.1463        | 3.0   | 105  | 1.3021          | 0.7071   | 0.7407    | 0.5970 | 0.6612 |
| 0.1664        | 4.0   | 140  | 1.1251          | 0.6857   | 0.6825    | 0.6418 | 0.6615 |
| 0.1746        | 5.0   | 175  | 0.8354          | 0.7214   | 0.7692    | 0.5970 | 0.6723 |
| 0.2282        | 6.0   | 210  | 1.2394          | 0.6929   | 0.6935    | 0.6418 | 0.6667 |
| 0.103         | 7.0   | 245  | 1.3935          | 0.6857   | 0.6769    | 0.6567 | 0.6667 |
| 0.186         | 8.0   | 280  | 1.1753          | 0.7      | 0.6812    | 0.7015 | 0.6912 |
| 0.2189        | 9.0   | 315  | 1.1819          | 0.6929   | 0.7069    | 0.6119 | 0.6560 |
| 0.1476        | 10.0  | 350  | 1.4722          | 0.65     | 0.65      | 0.5821 | 0.6142 |
| 0.2055        | 11.0  | 385  | 0.7656          | 0.7571   | 0.7895    | 0.6716 | 0.7258 |
| 0.1607        | 12.0  | 420  | 0.9756          | 0.7071   | 0.76      | 0.5672 | 0.6496 |
| 0.1532        | 13.0  | 455  | 0.9945          | 0.7071   | 0.7031    | 0.6716 | 0.6870 |
| 0.1023        | 14.0  | 490  | 1.1967          | 0.7071   | 0.7031    | 0.6716 | 0.6870 |
| 0.2389        | 15.0  | 525  | 0.7984          | 0.7643   | 0.7742    | 0.7164 | 0.7442 |
| 0.1925        | 16.0  | 560  | 0.9343          | 0.7143   | 0.7368    | 0.6269 | 0.6774 |
| 0.2038        | 17.0  | 595  | 1.1440          | 0.6857   | 0.6949    | 0.6119 | 0.6508 |
| 0.2193        | 18.0  | 630  | 0.9709          | 0.7071   | 0.7167    | 0.6418 | 0.6772 |
| 0.1719        | 19.0  | 665  | 0.9007          | 0.7429   | 0.7818    | 0.6418 | 0.7049 |
| 0.2334        | 20.0  | 700  | 0.8711          | 0.7429   | 0.7818    | 0.6418 | 0.7049 |
| 0.131         | 21.0  | 735  | 1.0785          | 0.7143   | 0.7288    | 0.6418 | 0.6825 |
| 0.2316        | 22.0  | 770  | 1.1080          | 0.6643   | 0.6786    | 0.5672 | 0.6179 |
| 0.1815        | 23.0  | 805  | 1.2657          | 0.6929   | 0.7308    | 0.5672 | 0.6387 |
| 0.1521        | 24.0  | 840  | 1.2584          | 0.7      | 0.6812    | 0.7015 | 0.6912 |
| 0.244         | 25.0  | 875  | 1.0375          | 0.7786   | 0.7812    | 0.7463 | 0.7634 |
| 0.3668        | 26.0  | 910  | 1.1253          | 0.7286   | 0.7458    | 0.6567 | 0.6984 |
| 0.1564        | 27.0  | 945  | 0.9891          | 0.7214   | 0.7414    | 0.6418 | 0.688  |
| 0.1782        | 28.0  | 980  | 0.9936          | 0.7357   | 0.75      | 0.6716 | 0.7087 |
| 0.1945        | 29.0  | 1015 | 0.9586          | 0.7357   | 0.7419    | 0.6866 | 0.7132 |
| 0.271         | 30.0  | 1050 | 0.8128          | 0.7357   | 0.7778    | 0.6269 | 0.6942 |
| 0.1889        | 31.0  | 1085 | 1.2141          | 0.6714   | 0.7059    | 0.5373 | 0.6102 |
| 0.1928        | 32.0  | 1120 | 1.0059          | 0.7143   | 0.7368    | 0.6269 | 0.6774 |
| 0.2035        | 33.0  | 1155 | 1.1185          | 0.6929   | 0.7069    | 0.6119 | 0.6560 |
| 0.226         | 34.0  | 1190 | 1.1719          | 0.6286   | 0.6271    | 0.5522 | 0.5873 |
| 0.1801        | 35.0  | 1225 | 1.1689          | 0.6786   | 0.6719    | 0.6418 | 0.6565 |
| 0.2353        | 36.0  | 1260 | 1.1392          | 0.7      | 0.6923    | 0.6716 | 0.6818 |
| 0.1686        | 37.0  | 1295 | 1.2064          | 0.6429   | 0.6667    | 0.5075 | 0.5763 |
| 0.2278        | 38.0  | 1330 | 0.8528          | 0.75     | 0.7759    | 0.6716 | 0.7200 |
| 0.1905        | 39.0  | 1365 | 1.2736          | 0.6643   | 0.6786    | 0.5672 | 0.6179 |
| 0.2136        | 40.0  | 1400 | 1.0255          | 0.7214   | 0.7333    | 0.6567 | 0.6929 |
| 0.1544        | 41.0  | 1435 | 0.9427          | 0.7214   | 0.7333    | 0.6567 | 0.6929 |
| 0.2691        | 42.0  | 1470 | 1.0433          | 0.7286   | 0.7544    | 0.6418 | 0.6935 |
| 0.2804        | 43.0  | 1505 | 1.2006          | 0.6929   | 0.7143    | 0.5970 | 0.6504 |
| 0.2345        | 44.0  | 1540 | 0.9487          | 0.75     | 0.7857    | 0.6567 | 0.7154 |
| 0.2541        | 45.0  | 1575 | 0.9468          | 0.7429   | 0.7246    | 0.7463 | 0.7353 |
| 0.2718        | 46.0  | 1610 | 1.3955          | 0.6714   | 0.6909    | 0.5672 | 0.6230 |
| 0.3179        | 47.0  | 1645 | 1.3356          | 0.6786   | 0.7037    | 0.5672 | 0.6281 |
| 0.4808        | 48.0  | 1680 | 0.9297          | 0.7429   | 0.7719    | 0.6567 | 0.7097 |
| 0.3231        | 49.0  | 1715 | 0.8732          | 0.7429   | 0.7818    | 0.6418 | 0.7049 |
| 0.3681        | 50.0  | 1750 | 1.0578          | 0.6857   | 0.7255    | 0.5522 | 0.6271 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1