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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: indolem/indobert-base-uncased
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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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+ - f1
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+ - recall
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+ - precision
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+ model-index:
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+ - name: indobert_sarcasm
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+ results: []
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+ ---
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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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+
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/arthad24/emotion_analysis_V2/runs/l0kjyqxw)
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+ # indobert_sarcasm
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+
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+ This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5596
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+ - Accuracy: 0.7997
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+ - F1: 0.7226
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+ - Recall: 0.7148
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+ - Precision: 0.7326
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - eval_batch_size: 32
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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: 0.1
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+ - num_epochs: 4
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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+ | 0.5348 | 1.0 | 385 | 0.4679 | 0.7815 | 0.5831 | 0.5821 | 0.7724 |
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+ | 0.4424 | 2.0 | 770 | 0.4659 | 0.8016 | 0.6838 | 0.6619 | 0.7529 |
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+ | 0.3403 | 3.0 | 1155 | 0.4683 | 0.8 | 0.7026 | 0.6851 | 0.7377 |
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+ | 0.2386 | 4.0 | 1540 | 0.5596 | 0.7997 | 0.7226 | 0.7148 | 0.7326 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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