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+ ---
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+ license: mit
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+ base_model: tangminhanh/ts_cate
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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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+ - precision
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+ - recall
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+ model-index:
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+ - name: ts_subcate
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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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+ # ts_subcate
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+
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+ This model is a fine-tuned version of [tangminhanh/ts_cate](https://huggingface.co/tangminhanh/ts_cate) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0084
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+ - Accuracy: 0.7013
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+ - F1: 0.7812
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+ - Precision: 0.8815
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+ - Recall: 0.7014
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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: 32
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+ - eval_batch_size: 64
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 403 | 0.0261 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0805 | 2.0 | 806 | 0.0174 | 0.3328 | 0.4904 | 0.9438 | 0.3313 |
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+ | 0.0203 | 3.0 | 1209 | 0.0131 | 0.4702 | 0.6217 | 0.9229 | 0.4687 |
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+ | 0.0138 | 4.0 | 1612 | 0.0111 | 0.5592 | 0.6939 | 0.9170 | 0.5581 |
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+ | 0.0104 | 5.0 | 2015 | 0.0100 | 0.6297 | 0.7417 | 0.8998 | 0.6308 |
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+ | 0.0104 | 6.0 | 2418 | 0.0091 | 0.6659 | 0.7628 | 0.8909 | 0.6669 |
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+ | 0.0084 | 7.0 | 2821 | 0.0088 | 0.6815 | 0.7712 | 0.8867 | 0.6823 |
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+ | 0.0072 | 8.0 | 3224 | 0.0086 | 0.6889 | 0.7764 | 0.8874 | 0.6900 |
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+ | 0.0063 | 9.0 | 3627 | 0.0084 | 0.6982 | 0.7803 | 0.8832 | 0.6989 |
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+ | 0.006 | 10.0 | 4030 | 0.0084 | 0.7013 | 0.7812 | 0.8815 | 0.7014 |
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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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