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pd_subcate

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pd_subcate

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  1. README.md +16 -15
  2. model.safetensors +1 -1
  3. runs/Jul30_08-25-48_06a218ada6c5/events.out.tfevents.1722327952.06a218ada6c5.1464.14 +3 -0
  4. runs/Jul30_08-25-48_06a218ada6c5/events.out.tfevents.1722328453.06a218ada6c5.1464.15 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [tangminhanh/pd_cate](https://huggingface.co/tangminhanh/pd_cate) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0817
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- - Accuracy: 0.0626
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- - F1: 0.1103
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- - Precision: 0.4717
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- - Recall: 0.0624
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  ## Model description
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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: 8
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  ### Training results
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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 | 100 | 0.1179 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 2.0 | 200 | 0.1039 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 3.0 | 300 | 0.0949 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 4.0 | 400 | 0.0888 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.1312 | 5.0 | 500 | 0.0852 | 0.0113 | 0.0217 | 0.3333 | 0.0112 |
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- | 0.1312 | 6.0 | 600 | 0.0838 | 0.0413 | 0.0758 | 0.4714 | 0.0412 |
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- | 0.1312 | 7.0 | 700 | 0.0820 | 0.0601 | 0.1062 | 0.4660 | 0.0599 |
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- | 0.1312 | 8.0 | 800 | 0.0817 | 0.0626 | 0.1103 | 0.4717 | 0.0624 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [tangminhanh/pd_cate](https://huggingface.co/tangminhanh/pd_cate) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0784
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+ - Accuracy: 0.2315
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+ - F1: 0.3214
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+ - Precision: 0.4825
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+ - Recall: 0.2409
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  ## Model description
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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: 64
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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: 9
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  ### Training results
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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 | 50 | 0.0799 | 0.1051 | 0.1692 | 0.4375 | 0.1049 |
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+ | No log | 2.0 | 100 | 0.0787 | 0.1377 | 0.2156 | 0.4706 | 0.1398 |
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+ | No log | 3.0 | 150 | 0.0792 | 0.1940 | 0.3093 | 0.4583 | 0.2335 |
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+ | No log | 4.0 | 200 | 0.0781 | 0.1877 | 0.2732 | 0.4796 | 0.1910 |
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+ | No log | 5.0 | 250 | 0.0778 | 0.2090 | 0.2977 | 0.4985 | 0.2122 |
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+ | No log | 6.0 | 300 | 0.0782 | 0.2190 | 0.3005 | 0.4695 | 0.2210 |
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+ | No log | 7.0 | 350 | 0.0781 | 0.2290 | 0.3120 | 0.4805 | 0.2310 |
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+ | No log | 8.0 | 400 | 0.0783 | 0.2390 | 0.3191 | 0.4823 | 0.2385 |
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+ | No log | 9.0 | 450 | 0.0784 | 0.2315 | 0.3214 | 0.4825 | 0.2409 |
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  ### Framework versions
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