---
license: apache-2.0
tags:
- classification
- sentiment
- sinhala
- news data
- generated_from_trainer
base_model: albert-base-v2
model-index:
- name: sinhala_albert
  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. -->

# sinhala_albert

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.5337

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0056        | 1.0   | 83   | 1.0130          |
| 0.9992        | 2.0   | 166  | 1.0021          |
| 0.9774        | 3.0   | 249  | 0.9789          |
| 0.9323        | 4.0   | 332  | 0.9695          |
| 0.863         | 5.0   | 415  | 0.9616          |
| 0.7944        | 6.0   | 498  | 0.9871          |
| 0.6328        | 7.0   | 581  | 1.0075          |
| 0.4705        | 8.0   | 664  | 1.4911          |
| 0.2834        | 9.0   | 747  | 1.5777          |
| 0.2278        | 10.0  | 830  | 1.6406          |
| 0.1751        | 11.0  | 913  | 1.7568          |
| 0.1657        | 12.0  | 996  | 1.7089          |
| 0.0974        | 13.0  | 1079 | 1.8463          |
| 0.1562        | 14.0  | 1162 | 1.9219          |
| 0.118         | 15.0  | 1245 | 1.9384          |
| 0.1044        | 16.0  | 1328 | 1.9971          |
| 0.0952        | 17.0  | 1411 | 2.1732          |
| 0.0877        | 18.0  | 1494 | 2.0566          |
| 0.0598        | 19.0  | 1577 | 2.4616          |
| 0.0762        | 20.0  | 1660 | 2.2672          |
| 0.1003        | 21.0  | 1743 | 2.3471          |
| 0.0627        | 22.0  | 1826 | 2.2526          |
| 0.0584        | 23.0  | 1909 | 2.7092          |
| 0.0679        | 24.0  | 1992 | 2.1629          |
| 0.0538        | 25.0  | 2075 | 2.5745          |
| 0.0723        | 26.0  | 2158 | 2.5667          |
| 0.0564        | 27.0  | 2241 | 2.4331          |
| 0.0662        | 28.0  | 2324 | 2.7811          |
| 0.0226        | 29.0  | 2407 | 2.8163          |
| 0.0224        | 30.0  | 2490 | 2.7452          |
| 0.0344        | 31.0  | 2573 | 2.6642          |
| 0.0519        | 32.0  | 2656 | 2.3490          |
| 0.0478        | 33.0  | 2739 | 2.7382          |
| 0.0436        | 34.0  | 2822 | 2.7556          |
| 0.0474        | 35.0  | 2905 | 2.5449          |
| 0.0355        | 36.0  | 2988 | 2.8280          |
| 0.0343        | 37.0  | 3071 | 2.9405          |
| 0.0283        | 38.0  | 3154 | 2.9870          |
| 0.0446        | 39.0  | 3237 | 3.0252          |
| 0.0288        | 40.0  | 3320 | 3.0866          |
| 0.0134        | 41.0  | 3403 | 3.1549          |
| 0.0328        | 42.0  | 3486 | 3.0168          |
| 0.0159        | 43.0  | 3569 | 2.8753          |
| 0.0155        | 44.0  | 3652 | 3.3455          |
| 0.0087        | 45.0  | 3735 | 3.4373          |
| 0.0296        | 46.0  | 3818 | 3.1949          |
| 0.0085        | 47.0  | 3901 | 3.1817          |
| 0.0048        | 48.0  | 3984 | 3.2233          |
| 0.0122        | 49.0  | 4067 | 3.5465          |
| 0.0024        | 50.0  | 4150 | 3.5276          |
| 0.0014        | 51.0  | 4233 | 3.5111          |
| 0.0121        | 52.0  | 4316 | 3.4483          |
| 0.0159        | 53.0  | 4399 | 3.8072          |
| 0.0027        | 54.0  | 4482 | 3.7448          |
| 0.0059        | 55.0  | 4565 | 3.9230          |
| 0.0083        | 56.0  | 4648 | 3.9245          |
| 0.0128        | 57.0  | 4731 | 3.8699          |
| 0.0116        | 58.0  | 4814 | 3.9957          |
| 0.0013        | 59.0  | 4897 | 3.8153          |
| 0.0013        | 60.0  | 4980 | 3.9093          |
| 0.0035        | 61.0  | 5063 | 4.0339          |
| 0.0028        | 62.0  | 5146 | 3.9929          |
| 0.0036        | 63.0  | 5229 | 4.1217          |
| 0.004         | 64.0  | 5312 | 4.0936          |
| 0.0014        | 65.0  | 5395 | 4.1109          |
| 0.0047        | 66.0  | 5478 | 4.1978          |
| 0.0005        | 67.0  | 5561 | 4.2320          |
| 0.0009        | 68.0  | 5644 | 4.2441          |
| 0.0027        | 69.0  | 5727 | 4.2670          |
| 0.0008        | 70.0  | 5810 | 4.2923          |
| 0.0013        | 71.0  | 5893 | 4.3101          |
| 0.0006        | 72.0  | 5976 | 4.3561          |
| 0.0024        | 73.0  | 6059 | 4.3419          |
| 0.0014        | 74.0  | 6142 | 4.3432          |
| 0.0011        | 75.0  | 6225 | 4.3302          |
| 0.0           | 76.0  | 6308 | 4.3439          |
| 0.0016        | 77.0  | 6391 | 4.3667          |
| 0.0026        | 78.0  | 6474 | 4.3803          |
| 0.0031        | 79.0  | 6557 | 4.3800          |
| 0.002         | 80.0  | 6640 | 4.3941          |
| 0.0008        | 81.0  | 6723 | 4.4071          |
| 0.0019        | 82.0  | 6806 | 4.4259          |
| 0.0013        | 83.0  | 6889 | 4.4436          |
| 0.0015        | 84.0  | 6972 | 4.4603          |
| 0.0009        | 85.0  | 7055 | 4.4706          |
| 0.0019        | 86.0  | 7138 | 4.4701          |
| 0.001         | 87.0  | 7221 | 4.4777          |
| 0.0007        | 88.0  | 7304 | 4.4905          |
| 0.0021        | 89.0  | 7387 | 4.4910          |
| 0.0012        | 90.0  | 7470 | 4.4959          |
| 0.0           | 91.0  | 7553 | 4.4990          |
| 0.0024        | 92.0  | 7636 | 4.5091          |
| 0.0031        | 93.0  | 7719 | 4.5115          |
| 0.0011        | 94.0  | 7802 | 4.5215          |
| 0.0           | 95.0  | 7885 | 4.5152          |
| 0.002         | 96.0  | 7968 | 4.5200          |
| 0.0013        | 97.0  | 8051 | 4.5293          |
| 0.0013        | 98.0  | 8134 | 4.5285          |
| 0.0023        | 99.0  | 8217 | 4.5339          |
| 0.002         | 100.0 | 8300 | 4.5337          |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu118
- Datasets 2.14.5
- Tokenizers 0.19.1