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bert-30M-uncased-classification-CMC-fqa-new

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  1. README.md +109 -0
  2. model.safetensors +1 -1
  3. runs/Jan27_17-50-08_6053dd9424d3/events.out.tfevents.1706377813.6053dd9424d3.443.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: vietgpt/bert-30M-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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+ model-index:
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+ - name: bert-30M-uncased-classification-CMC-fqa-new
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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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+ # bert-30M-uncased-classification-CMC-fqa-new
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+
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+ This model is a fine-tuned version of [vietgpt/bert-30M-uncased](https://huggingface.co/vietgpt/bert-30M-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7760
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+ - Accuracy: 0.9677
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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: 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: 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 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 20 | 3.4306 | 0.0323 |
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+ | No log | 2.0 | 40 | 3.4143 | 0.0323 |
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+ | No log | 3.0 | 60 | 3.4026 | 0.0645 |
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+ | No log | 4.0 | 80 | 3.3888 | 0.2258 |
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+ | No log | 5.0 | 100 | 3.3725 | 0.2581 |
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+ | No log | 6.0 | 120 | 3.3523 | 0.3548 |
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+ | No log | 7.0 | 140 | 3.3244 | 0.4194 |
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+ | No log | 8.0 | 160 | 3.2797 | 0.3871 |
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+ | No log | 9.0 | 180 | 3.2072 | 0.5161 |
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+ | No log | 10.0 | 200 | 3.0977 | 0.4839 |
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+ | No log | 11.0 | 220 | 2.9538 | 0.2903 |
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+ | No log | 12.0 | 240 | 2.8136 | 0.2903 |
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+ | No log | 13.0 | 260 | 2.6977 | 0.3871 |
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+ | No log | 14.0 | 280 | 2.5970 | 0.4839 |
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+ | No log | 15.0 | 300 | 2.5041 | 0.5806 |
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+ | No log | 16.0 | 320 | 2.4092 | 0.5484 |
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+ | No log | 17.0 | 340 | 2.3064 | 0.6774 |
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+ | No log | 18.0 | 360 | 2.2057 | 0.6774 |
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+ | No log | 19.0 | 380 | 2.0945 | 0.7419 |
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+ | No log | 20.0 | 400 | 1.9827 | 0.7742 |
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+ | No log | 21.0 | 420 | 1.8641 | 0.7742 |
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+ | No log | 22.0 | 440 | 1.7476 | 0.7742 |
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+ | No log | 23.0 | 460 | 1.6518 | 0.8065 |
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+ | No log | 24.0 | 480 | 1.5613 | 0.8065 |
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+ | 2.7559 | 25.0 | 500 | 1.4894 | 0.8387 |
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+ | 2.7559 | 26.0 | 520 | 1.4089 | 0.8387 |
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+ | 2.7559 | 27.0 | 540 | 1.3390 | 0.8065 |
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+ | 2.7559 | 28.0 | 560 | 1.2802 | 0.8710 |
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+ | 2.7559 | 29.0 | 580 | 1.2265 | 0.8710 |
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+ | 2.7559 | 30.0 | 600 | 1.1639 | 0.8387 |
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+ | 2.7559 | 31.0 | 620 | 1.1253 | 0.8710 |
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+ | 2.7559 | 32.0 | 640 | 1.0845 | 0.9032 |
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+ | 2.7559 | 33.0 | 660 | 1.0468 | 0.9032 |
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+ | 2.7559 | 34.0 | 680 | 1.0144 | 0.9032 |
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+ | 2.7559 | 35.0 | 700 | 0.9805 | 0.9355 |
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+ | 2.7559 | 36.0 | 720 | 0.9564 | 0.9355 |
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+ | 2.7559 | 37.0 | 740 | 0.9237 | 0.9677 |
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+ | 2.7559 | 38.0 | 760 | 0.9041 | 0.9355 |
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+ | 2.7559 | 39.0 | 780 | 0.8815 | 0.9677 |
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+ | 2.7559 | 40.0 | 800 | 0.8668 | 0.9677 |
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+ | 2.7559 | 41.0 | 820 | 0.8486 | 0.9677 |
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+ | 2.7559 | 42.0 | 840 | 0.8288 | 0.9677 |
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+ | 2.7559 | 43.0 | 860 | 0.8174 | 0.9677 |
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+ | 2.7559 | 44.0 | 880 | 0.8058 | 0.9677 |
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+ | 2.7559 | 45.0 | 900 | 0.7978 | 0.9677 |
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+ | 2.7559 | 46.0 | 920 | 0.7901 | 0.9677 |
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+ | 2.7559 | 47.0 | 940 | 0.7842 | 0.9677 |
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+ | 2.7559 | 48.0 | 960 | 0.7798 | 0.9677 |
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+ | 2.7559 | 49.0 | 980 | 0.7769 | 0.9677 |
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+ | 1.1031 | 50.0 | 1000 | 0.7760 | 0.9677 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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