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pholarge

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: vinai/phobert-large
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: pholarge
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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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+ # pholarge
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+
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+ This model is a fine-tuned version of [vinai/phobert-large](https://huggingface.co/vinai/phobert-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8918
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+ - F1: 0.6410
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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: 3e-05
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+ - train_batch_size: 24
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+ - eval_batch_size: 24
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 40.0
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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 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 0.3094 | 1.0 | 1033 | 0.2295 | 0.9327 |
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+ | 0.2346 | 2.0 | 2066 | 0.2651 | 0.9280 |
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+ | 0.2359 | 3.0 | 3099 | 0.2357 | 0.9338 |
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+ | 0.1734 | 4.0 | 4132 | 0.2720 | 0.9277 |
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+ | 0.1551 | 5.0 | 5165 | 0.2940 | 0.9350 |
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+ | 0.1282 | 6.0 | 6198 | 0.2752 | 0.9361 |
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+ | 0.1208 | 7.0 | 7231 | 0.3137 | 0.9347 |
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+ | 0.1074 | 8.0 | 8264 | 0.2967 | 0.9355 |
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+ | 0.2719 | 9.0 | 9297 | 0.8269 | 0.6410 |
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+ | 0.8456 | 10.0 | 10330 | 0.8220 | 0.6410 |
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+ | 0.84 | 11.0 | 11363 | 0.8212 | 0.6410 |
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+ | 0.841 | 12.0 | 12396 | 0.8207 | 0.6410 |
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+ | 0.8383 | 13.0 | 13429 | 0.8198 | 0.6410 |
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+ | 0.8371 | 14.0 | 14462 | 0.8276 | 0.6410 |
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+ | 0.8486 | 15.0 | 15495 | 0.8244 | 0.6410 |
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+ | 0.844 | 16.0 | 16528 | 0.8391 | 0.6410 |
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+ | 0.837 | 17.0 | 17561 | 0.8235 | 0.6410 |
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+ | 0.8438 | 18.0 | 18594 | 0.8247 | 0.6410 |
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+ | 0.8418 | 19.0 | 19627 | 0.8237 | 0.6410 |
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+ | 0.8384 | 20.0 | 20660 | 0.8199 | 0.6410 |
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+ | 0.8387 | 21.0 | 21693 | 0.8226 | 0.6410 |
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+ | 0.8478 | 22.0 | 22726 | 0.8205 | 0.6410 |
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+ | 0.8364 | 23.0 | 23759 | 0.8259 | 0.6410 |
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+ | 0.8325 | 24.0 | 24792 | 0.8245 | 0.6410 |
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+ | 0.8289 | 25.0 | 25825 | 0.8248 | 0.6410 |
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+ | 0.8251 | 26.0 | 26858 | 0.8247 | 0.6410 |
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+ | 0.824 | 27.0 | 27891 | 0.8214 | 0.6410 |
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+ | 0.8197 | 28.0 | 28924 | 0.8282 | 0.6410 |
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+ | 0.8241 | 29.0 | 29957 | 0.8340 | 0.6410 |
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+ | 0.8285 | 30.0 | 30990 | 0.8360 | 0.6410 |
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+ | 0.8169 | 31.0 | 32023 | 0.8401 | 0.6410 |
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+ | 0.811 | 32.0 | 33056 | 0.8534 | 0.6410 |
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+ | 0.8056 | 33.0 | 34089 | 0.8690 | 0.6410 |
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+ | 0.8023 | 34.0 | 35122 | 0.8640 | 0.6410 |
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+ | 0.8146 | 35.0 | 36155 | 0.8704 | 0.6410 |
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+ | 0.8079 | 36.0 | 37188 | 0.8959 | 0.6410 |
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+ | 0.8081 | 37.0 | 38221 | 0.8802 | 0.6410 |
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+ | 0.8059 | 38.0 | 39254 | 0.8901 | 0.6410 |
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+ | 0.8045 | 39.0 | 40287 | 0.8882 | 0.6410 |
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+ | 0.8024 | 40.0 | 41320 | 0.8918 | 0.6410 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.0.dev0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.21.0
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