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indonesian_sentiment_sbert_base

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  1. README.md +47 -15
  2. model.safetensors +1 -1
  3. runs/Feb26_06-49-50_1670e0bb0f9b/events.out.tfevents.1708930191.1670e0bb0f9b.17494.1 +2 -2
  4. runs/Feb26_06-49-50_1670e0bb0f9b/events.out.tfevents.1708931974.1670e0bb0f9b.17494.2 +3 -0
README.md CHANGED
@@ -1,8 +1,9 @@
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  ---
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- license: mit
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- base_model: hanifnoerr/Fine-tuned-Indonesian-Sentiment-Classifier
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - accuracy
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  - precision
@@ -10,7 +11,29 @@ metrics:
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  - f1
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  model-index:
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  - name: sentiment
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,13 +41,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # sentiment
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- This model is a fine-tuned version of [hanifnoerr/Fine-tuned-Indonesian-Sentiment-Classifier](https://huggingface.co/hanifnoerr/Fine-tuned-Indonesian-Sentiment-Classifier) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6815
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- - Accuracy: 0.7266
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- - Precision: 0.7267
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- - Recall: 0.7266
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- - F1: 0.7267
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  ## Model description
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@@ -44,24 +67,33 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 2
 
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.7972 | 1.0 | 1301 | 0.6830 | 0.7120 | 0.7230 | 0.7120 | 0.7073 |
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- | 0.5085 | 2.0 | 2602 | 0.6815 | 0.7266 | 0.7267 | 0.7266 | 0.7267 |
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.37.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.17.1
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  - Tokenizers 0.15.2
 
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  ---
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+ base_model: naufalihsan/indonesian-sbert-large
 
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - indonlu
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  metrics:
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  - accuracy
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  - precision
 
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  - f1
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  model-index:
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  - name: sentiment
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: indonlu
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+ type: indonlu
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+ config: smsa
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+ split: validation
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+ args: smsa
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.95
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+ - name: Precision
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+ type: precision
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+ value: 0.9499758037063356
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+ - name: Recall
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+ type: recall
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+ value: 0.95
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+ - name: F1
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+ type: f1
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+ value: 0.9496487652420723
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # sentiment
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+ This model is a fine-tuned version of [naufalihsan/indonesian-sbert-large](https://huggingface.co/naufalihsan/indonesian-sbert-large) on the indonlu dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4450
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+ - Accuracy: 0.95
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+ - Precision: 0.9500
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+ - Recall: 0.95
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+ - F1: 0.9496
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 40
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+ - eval_batch_size: 40
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.01
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 275 | 0.2837 | 0.9405 | 0.9427 | 0.9405 | 0.9396 |
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+ | 0.0501 | 2.0 | 550 | 0.1966 | 0.9460 | 0.9468 | 0.9460 | 0.9458 |
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+ | 0.0501 | 3.0 | 825 | 0.2927 | 0.9437 | 0.9435 | 0.9437 | 0.9427 |
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+ | 0.0369 | 4.0 | 1100 | 0.3666 | 0.9460 | 0.9459 | 0.9460 | 0.9456 |
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+ | 0.0369 | 5.0 | 1375 | 0.3579 | 0.9468 | 0.9465 | 0.9468 | 0.9465 |
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+ | 0.0098 | 6.0 | 1650 | 0.4497 | 0.9476 | 0.9479 | 0.9476 | 0.9471 |
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+ | 0.0098 | 7.0 | 1925 | 0.4308 | 0.95 | 0.9501 | 0.95 | 0.9496 |
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+ | 0.0012 | 8.0 | 2200 | 0.4402 | 0.95 | 0.9499 | 0.95 | 0.9496 |
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+ | 0.0012 | 9.0 | 2475 | 0.4429 | 0.95 | 0.9500 | 0.95 | 0.9496 |
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+ | 0.0007 | 10.0 | 2750 | 0.4450 | 0.95 | 0.9500 | 0.95 | 0.9496 |
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  ### Framework versions
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+ - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.17.1
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  - Tokenizers 0.15.2
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