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ThuyNT03
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CS505-Classifier-T4_predictLabel_a1_v6

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+ ---
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+ base_model: vinai/phobert-base-v2
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: CS505-Classifier-T4_predictLabel_a1_v6
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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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+ # CS505-Classifier-T4_predictLabel_a1_v6
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+
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+ This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0014
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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: 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: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 0.98 | 48 | 0.6632 |
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+ | No log | 1.96 | 96 | 0.3136 |
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+ | No log | 2.94 | 144 | 0.2453 |
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+ | No log | 3.92 | 192 | 0.1673 |
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+ | No log | 4.9 | 240 | 0.1249 |
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+ | No log | 5.88 | 288 | 0.0850 |
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+ | No log | 6.86 | 336 | 0.0718 |
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+ | No log | 7.84 | 384 | 0.0576 |
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+ | No log | 8.82 | 432 | 0.0567 |
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+ | No log | 9.8 | 480 | 0.0530 |
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+ | 0.2878 | 10.78 | 528 | 0.0307 |
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+ | 0.2878 | 11.76 | 576 | 0.0376 |
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+ | 0.2878 | 12.73 | 624 | 0.0170 |
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+ | 0.2878 | 13.71 | 672 | 0.0195 |
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+ | 0.2878 | 14.69 | 720 | 0.0111 |
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+ | 0.2878 | 15.67 | 768 | 0.0131 |
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+ | 0.2878 | 16.65 | 816 | 0.0109 |
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+ | 0.2878 | 17.63 | 864 | 0.0073 |
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+ | 0.2878 | 18.61 | 912 | 0.0043 |
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+ | 0.2878 | 19.59 | 960 | 0.0032 |
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+ | 0.0238 | 20.57 | 1008 | 0.0067 |
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+ | 0.0238 | 21.55 | 1056 | 0.0027 |
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+ | 0.0238 | 22.53 | 1104 | 0.0025 |
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+ | 0.0238 | 23.51 | 1152 | 0.0025 |
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+ | 0.0238 | 24.49 | 1200 | 0.0022 |
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+ | 0.0238 | 25.47 | 1248 | 0.0022 |
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+ | 0.0238 | 26.45 | 1296 | 0.0021 |
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+ | 0.0238 | 27.43 | 1344 | 0.0020 |
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+ | 0.0238 | 28.41 | 1392 | 0.0019 |
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+ | 0.0238 | 29.39 | 1440 | 0.0019 |
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+ | 0.0238 | 30.37 | 1488 | 0.0018 |
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+ | 0.0036 | 31.35 | 1536 | 0.0018 |
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+ | 0.0036 | 32.33 | 1584 | 0.0018 |
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+ | 0.0036 | 33.31 | 1632 | 0.0017 |
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+ | 0.0036 | 34.29 | 1680 | 0.0017 |
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+ | 0.0036 | 35.27 | 1728 | 0.0016 |
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+ | 0.0036 | 36.24 | 1776 | 0.0017 |
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+ | 0.0036 | 37.22 | 1824 | 0.0016 |
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+ | 0.0036 | 38.2 | 1872 | 0.0016 |
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+ | 0.0036 | 39.18 | 1920 | 0.0015 |
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+ | 0.0036 | 40.16 | 1968 | 0.0015 |
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+ | 0.0022 | 41.14 | 2016 | 0.0015 |
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+ | 0.0022 | 42.12 | 2064 | 0.0015 |
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+ | 0.0022 | 43.1 | 2112 | 0.0015 |
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+ | 0.0022 | 44.08 | 2160 | 0.0015 |
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+ | 0.0022 | 45.06 | 2208 | 0.0015 |
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+ | 0.0022 | 46.04 | 2256 | 0.0015 |
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+ | 0.0022 | 47.02 | 2304 | 0.0015 |
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+ | 0.0022 | 48.0 | 2352 | 0.0015 |
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+ | 0.0022 | 48.98 | 2400 | 0.0014 |
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+ | 0.0022 | 49.96 | 2448 | 0.0014 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2