ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa-tuning
Browse files- README.md +66 -0
- config.json +37 -0
- model.safetensors +3 -0
- runs/May16_17-32-22_3ec345c9650e/events.out.tfevents.1715880742.3ec345c9650e.286.0 +3 -0
- runs/May16_17-32-35_3ec345c9650e/events.out.tfevents.1715880756.3ec345c9650e.286.1 +3 -0
- runs/May16_17-35-07_3ec345c9650e/events.out.tfevents.1715880910.3ec345c9650e.286.2 +3 -0
- runs/May16_17-37-07_3ec345c9650e/events.out.tfevents.1715881027.3ec345c9650e.2022.0 +3 -0
- runs/May16_17-41-33_3ec345c9650e/events.out.tfevents.1715881296.3ec345c9650e.2022.1 +3 -0
- runs/May16_17-41-33_3ec345c9650e/events.out.tfevents.1715882641.3ec345c9650e.2022.2 +3 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +59 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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license: mit
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base_model: ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa
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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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model-index:
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- name: output
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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
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should probably proofread and complete it, then remove this comment. -->
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# output
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This model is a fine-tuned version of [ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7283
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- Accuracy: 0.6978
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- F1 Score: 0.6979
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
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| 0.4822 | 1.0 | 1952 | 0.7514 | 0.6989 | 0.7001 |
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| 0.6036 | 2.0 | 3904 | 0.7232 | 0.7020 | 0.7030 |
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| 0.6004 | 3.0 | 5856 | 0.7226 | 0.7020 | 0.7027 |
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| 0.5904 | 4.0 | 7808 | 0.7260 | 0.7037 | 0.7046 |
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| 0.5919 | 5.0 | 9760 | 0.7250 | 0.7039 | 0.7048 |
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| 0.5939 | 6.0 | 11712 | 0.7260 | 0.7053 | 0.7060 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "negative",
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"1": "neutral",
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"2": "positive"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"negative": 0,
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"neutral": 1,
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"positive": 2
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.40.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 32000
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}
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model.safetensors
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runs/May16_17-41-33_3ec345c9650e/events.out.tfevents.1715881296.3ec345c9650e.2022.1
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special_tokens_map.json
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tokenizer.json
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tokenizer_config.json
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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vocab.txt
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