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yunase/DistilRoBertaModel_emotion_detection

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: distilroberta-base
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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: emotions_distilroberta
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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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+ # emotions_distilroberta
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+
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+ This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5345
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+ - F1 Micro: 0.6750
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+ - F1 Macro: 0.5924
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+ - Accuracy: 0.2078
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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: 0.0001
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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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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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
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+ | 0.7583 | 0.41 | 20 | 0.6581 | 0.5780 | 0.3558 | 0.1055 |
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+ | 0.6291 | 0.82 | 40 | 0.5893 | 0.6285 | 0.4836 | 0.1424 |
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+ | 0.5796 | 1.22 | 60 | 0.5759 | 0.6319 | 0.5261 | 0.1618 |
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+ | 0.5288 | 1.63 | 80 | 0.5409 | 0.6585 | 0.5526 | 0.1430 |
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+ | 0.5111 | 2.04 | 100 | 0.5339 | 0.6681 | 0.5648 | 0.1961 |
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+ | 0.4635 | 2.45 | 120 | 0.5291 | 0.6684 | 0.5714 | 0.1786 |
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+ | 0.4544 | 2.86 | 140 | 0.5282 | 0.6726 | 0.5787 | 0.1618 |
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+ | 0.4398 | 3.27 | 160 | 0.5281 | 0.6736 | 0.5833 | 0.2052 |
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+ | 0.3948 | 3.67 | 180 | 0.5309 | 0.6650 | 0.5896 | 0.1890 |
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+ | 0.41 | 4.08 | 200 | 0.5265 | 0.6785 | 0.5782 | 0.2168 |
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+ | 0.3722 | 4.49 | 220 | 0.5345 | 0.6750 | 0.5924 | 0.2078 |
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+ | 0.3617 | 4.9 | 240 | 0.5295 | 0.6769 | 0.5822 | 0.2155 |
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+ | 0.3362 | 5.31 | 260 | 0.5358 | 0.6696 | 0.5854 | 0.1851 |
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+ | 0.3204 | 5.71 | 280 | 0.5438 | 0.6762 | 0.5747 | 0.2097 |
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+ | 0.3194 | 6.12 | 300 | 0.5503 | 0.6764 | 0.5768 | 0.1832 |
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+ | 0.2921 | 6.53 | 320 | 0.5599 | 0.6734 | 0.5787 | 0.1961 |
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+ | 0.2938 | 6.94 | 340 | 0.5532 | 0.6753 | 0.5863 | 0.1806 |
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+ | 0.2708 | 7.35 | 360 | 0.5634 | 0.6735 | 0.5782 | 0.1922 |
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+ | 0.2625 | 7.76 | 380 | 0.5716 | 0.6727 | 0.5756 | 0.1961 |
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+ | 0.2565 | 8.16 | 400 | 0.5671 | 0.6739 | 0.5798 | 0.1922 |
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+ | 0.2403 | 8.57 | 420 | 0.5816 | 0.6688 | 0.5735 | 0.1728 |
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+ | 0.2466 | 8.98 | 440 | 0.5818 | 0.6739 | 0.5744 | 0.1871 |
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+ | 0.2331 | 9.39 | 460 | 0.5826 | 0.6722 | 0.5762 | 0.1922 |
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+ | 0.2233 | 9.8 | 480 | 0.5843 | 0.6738 | 0.5768 | 0.1942 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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+ "id2label": {
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+ "0": "anger",
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+ "1": "anticipation",
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+ "2": "disgust",
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+ "3": "fear",
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+ "4": "joy",
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+ "5": "love",
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+ "6": "optimism",
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+ "7": "pessimism",
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+ "8": "sadness",
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+ "9": "surprise",
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+ "10": "trust"
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+ "layer_norm_eps": 1e-05,
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+ "use_cache": true,
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+ }
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