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subcate-cs

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deberta-v2
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text-embeddings-inference
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subcate_cs

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  1. README.md +14 -19
  2. model.safetensors +1 -1
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  13. 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 [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0513
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- - Accuracy: 0.6829
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- - F1: 0.7101
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- - Precision: 0.7310
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- - Recall: 0.6903
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  ## Model description
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@@ -43,28 +43,23 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3e-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: 10
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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 | 390 | 0.0441 | 0.6207 | 0.6828 | 0.7423 | 0.6321 |
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- | 0.0398 | 2.0 | 780 | 0.0440 | 0.6226 | 0.6854 | 0.7485 | 0.6321 |
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- | 0.0314 | 3.0 | 1170 | 0.0429 | 0.6508 | 0.7038 | 0.7542 | 0.6596 |
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- | 0.0271 | 4.0 | 1560 | 0.0447 | 0.6547 | 0.7049 | 0.7560 | 0.6603 |
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- | 0.0271 | 5.0 | 1950 | 0.0460 | 0.6540 | 0.6997 | 0.7458 | 0.6590 |
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- | 0.0213 | 6.0 | 2340 | 0.0479 | 0.6656 | 0.7041 | 0.7365 | 0.6743 |
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- | 0.0169 | 7.0 | 2730 | 0.0491 | 0.6701 | 0.7060 | 0.7316 | 0.6820 |
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- | 0.0146 | 8.0 | 3120 | 0.0504 | 0.6759 | 0.7055 | 0.7263 | 0.6859 |
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- | 0.012 | 9.0 | 3510 | 0.0512 | 0.6797 | 0.7070 | 0.7281 | 0.6871 |
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- | 0.012 | 10.0 | 3900 | 0.0513 | 0.6829 | 0.7101 | 0.7310 | 0.6903 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0762
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+ - Accuracy: 0.6868
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+ - F1: 0.7105
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+ - Precision: 0.7235
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+ - Recall: 0.6980
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  ## Model description
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  ### Training hyperparameters
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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: 256
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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: 5
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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 | 98 | 0.0743 | 0.6887 | 0.7074 | 0.7103 | 0.7044 |
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+ | No log | 2.0 | 196 | 0.0753 | 0.6926 | 0.7141 | 0.7262 | 0.7025 |
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+ | No log | 3.0 | 294 | 0.0751 | 0.6829 | 0.7078 | 0.7219 | 0.6942 |
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+ | No log | 4.0 | 392 | 0.0774 | 0.6797 | 0.7009 | 0.7117 | 0.6903 |
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+ | No log | 5.0 | 490 | 0.0762 | 0.6868 | 0.7105 | 0.7235 | 0.6980 |
 
 
 
 
 
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  ### Framework versions
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