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vulnerability-severity-classification-roberta-base

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
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  1. README.md +7 -7
  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 [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5095
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- - Accuracy: 0.8245
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  ## Model description
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@@ -50,11 +50,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:------:|:---------------:|:--------:|
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- | 0.5087 | 1.0 | 26400 | 0.6427 | 0.7397 |
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- | 0.4433 | 2.0 | 52800 | 0.5840 | 0.7693 |
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- | 0.5995 | 3.0 | 79200 | 0.5373 | 0.7951 |
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- | 0.4051 | 4.0 | 105600 | 0.5059 | 0.8154 |
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- | 0.38 | 5.0 | 132000 | 0.5095 | 0.8245 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5043
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+ - Accuracy: 0.8266
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:------:|:---------------:|:--------:|
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+ | 0.6699 | 1.0 | 26473 | 0.6352 | 0.7442 |
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+ | 0.5909 | 2.0 | 52946 | 0.5688 | 0.7736 |
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+ | 0.4787 | 3.0 | 79419 | 0.5192 | 0.7981 |
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+ | 0.4534 | 4.0 | 105892 | 0.5025 | 0.8174 |
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+ | 0.3843 | 5.0 | 132365 | 0.5043 | 0.8266 |
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  ### Framework versions
emissions.csv CHANGED
@@ -1,2 +1,2 @@
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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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model.safetensors CHANGED
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