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vulnerability-severity-classification-chinese-macbert-base

Text Classification
Transformers
Safetensors
Chinese
bert
Generated from Trainer
classification
nlp
chinese
vulnerability
text-embeddings-inference
Model card Files
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Community
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End of training

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Files changed (3) hide show
  1. README.md +13 -13
  2. emissions.csv +1 -1
  3. model.safetensors +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [hfl/chinese-macbert-base](https://huggingface.co/hfl/chinese-macbert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6118
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- - Accuracy: 0.7832
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  ## Model description
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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: 32
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- - eval_batch_size: 32
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.5706 | 1.0 | 3511 | 0.5875 | 0.7503 |
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- | 0.5364 | 2.0 | 7022 | 0.5596 | 0.7702 |
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- | 0.5483 | 3.0 | 10533 | 0.5518 | 0.7768 |
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- | 0.4161 | 4.0 | 14044 | 0.5757 | 0.7838 |
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- | 0.351 | 5.0 | 17555 | 0.6118 | 0.7832 |
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  ### Framework versions
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- - Transformers 4.57.1
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  - Pytorch 2.9.1+cu128
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- - Datasets 4.4.1
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  - Tokenizers 0.22.1
 
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  This model is a fine-tuned version of [hfl/chinese-macbert-base](https://huggingface.co/hfl/chinese-macbert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6059
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+ - Accuracy: 0.7771
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  ## Model description
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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: 64
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+ - eval_batch_size: 64
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5764 | 1.0 | 1772 | 0.6157 | 0.7462 |
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+ | 0.5644 | 2.0 | 3544 | 0.5618 | 0.7663 |
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+ | 0.4589 | 3.0 | 5316 | 0.5615 | 0.7781 |
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+ | 0.3881 | 4.0 | 7088 | 0.5791 | 0.7823 |
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+ | 0.3433 | 5.0 | 8860 | 0.6059 | 0.7771 |
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  ### Framework versions
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+ - Transformers 4.57.3
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  - Pytorch 2.9.1+cu128
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+ - Datasets 4.4.2
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  - Tokenizers 0.22.1
emissions.csv CHANGED
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  timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
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