luthfi507/text-classification

1---2license: mit3base_model: indobenchmark/indobert-base-p14tags:5- generated_from_trainer6model-index:7- name: text-classification8  results: []9---10 11<!-- This model card has been generated automatically according to the information the Trainer had access to. You12should probably proofread and complete it, then remove this comment. -->13 14# text-classification15 16This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on the None dataset.17It achieves the following results on the evaluation set:18- Loss: 0.459019- Balanced Accuracy: 0.686820 21## Model description22 23More information needed24 25## Intended uses & limitations26 27More information needed28 29## Training and evaluation data30 31More information needed32 33## Training procedure34 35### Training hyperparameters36 37The following hyperparameters were used during training:38- learning_rate: 5e-0539- train_batch_size: 3240- eval_batch_size: 3241- seed: 4242- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0843- lr_scheduler_type: linear44- num_epochs: 1045 46### Training results47 48| Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy |49|:-------------:|:-----:|:----:|:---------------:|:-----------------:|50| No log        | 1.0   | 125  | 0.4590          | 0.6868            |51| No log        | 2.0   | 250  | 0.5104          | 0.6470            |52| No log        | 3.0   | 375  | 0.5941          | 0.6448            |53| 0.3146        | 4.0   | 500  | 0.5873          | 0.7828            |54| 0.3146        | 5.0   | 625  | 0.6645          | 0.8005            |55| 0.3146        | 6.0   | 750  | 0.6635          | 0.8110            |56| 0.3146        | 7.0   | 875  | 0.6684          | 0.7801            |57| 0.0956        | 8.0   | 1000 | 0.8031          | 0.7786            |58| 0.0956        | 9.0   | 1125 | 0.7523          | 0.7827            |59| 0.0956        | 10.0  | 1250 | 0.7878          | 0.7715            |60 61 62### Framework versions63 64- Transformers 4.41.265- Pytorch 2.3.0+cu12166- Datasets 2.19.267- Tokenizers 0.19.168