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ThuyNT03
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CS505-Classifier-T4_predictLabel_a1

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  1. README.md +22 -12
  2. model.safetensors +1 -1
  3. runs/Mar10_10-33-09_e4fb50e4764c/events.out.tfevents.1710066790.e4fb50e4764c.219.1 +2 -2
README.md CHANGED
@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1123
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  ## Model description
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@@ -39,22 +39,32 @@ The following hyperparameters were used during training:
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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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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 0.98 | 48 | 1.0265 |
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- | No log | 1.96 | 96 | 0.5901 |
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- | No log | 2.94 | 144 | 0.3601 |
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- | No log | 3.92 | 192 | 0.2500 |
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- | No log | 4.9 | 240 | 0.2089 |
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- | No log | 5.88 | 288 | 0.1765 |
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- | No log | 6.86 | 336 | 0.1441 |
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- | No log | 7.84 | 384 | 0.1320 |
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- | No log | 8.82 | 432 | 0.1174 |
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- | No log | 9.8 | 480 | 0.1123 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0155
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  ## Model description
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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: 20
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 0.98 | 48 | 1.0473 |
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+ | No log | 1.96 | 96 | 0.5664 |
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+ | No log | 2.94 | 144 | 0.3371 |
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+ | No log | 3.92 | 192 | 0.2277 |
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+ | No log | 4.9 | 240 | 0.1850 |
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+ | No log | 5.88 | 288 | 0.1451 |
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+ | No log | 6.86 | 336 | 0.1126 |
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+ | No log | 7.84 | 384 | 0.0853 |
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+ | No log | 8.82 | 432 | 0.0635 |
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+ | No log | 9.8 | 480 | 0.0598 |
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+ | 0.4029 | 10.78 | 528 | 0.0407 |
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+ | 0.4029 | 11.76 | 576 | 0.0337 |
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+ | 0.4029 | 12.73 | 624 | 0.0300 |
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+ | 0.4029 | 13.71 | 672 | 0.0270 |
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+ | 0.4029 | 14.69 | 720 | 0.0209 |
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+ | 0.4029 | 15.67 | 768 | 0.0196 |
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+ | 0.4029 | 16.65 | 816 | 0.0205 |
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+ | 0.4029 | 17.63 | 864 | 0.0181 |
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+ | 0.4029 | 18.61 | 912 | 0.0160 |
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+ | 0.4029 | 19.59 | 960 | 0.0155 |
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  ### Framework versions
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