End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: hfl/chinese-macbert-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: vulnerability-severity-classification-chinese-macbert-base-test
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# vulnerability-severity-classification-chinese-macbert-base-test
+
+This model is a fine-tuned version of [hfl/chinese-macbert-base](https://huggingface.co/hfl/chinese-macbert-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8342
+- Accuracy: 0.7323
+- F1 Macro: 0.6756
+- Low Precision: 0.4336
+- Low Recall: 0.6084
+- Low F1: 0.5064
+- Medium Precision: 0.8150
+- Medium Recall: 0.7024
+- Medium F1: 0.7545
+- High Precision: 0.7263
+- High Recall: 0.8099
+- High F1: 0.7658
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 3e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Low Precision | Low Recall | Low F1 | Medium Precision | Medium Recall | Medium F1 | High Precision | High Recall | High F1 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-------------:|:----------:|:------:|:----------------:|:-------------:|:---------:|:--------------:|:-----------:|:-------:|
+| 0.7148        | 1.0   | 1590 | 0.7313          | 0.6901   | 0.6344   | 0.3572        | 0.6132     | 0.4514 | 0.7990           | 0.6245        | 0.7010    | 0.6984         | 0.8115      | 0.7507  |
+| 0.7214        | 2.0   | 3180 | 0.6823          | 0.6980   | 0.6448   | 0.3467        | 0.6795     | 0.4591 | 0.8066           | 0.6398        | 0.7136    | 0.7323         | 0.7934      | 0.7616  |
+| 0.4822        | 3.0   | 4770 | 0.6937          | 0.6999   | 0.6464   | 0.3403        | 0.6934     | 0.4566 | 0.8303           | 0.6258        | 0.7137    | 0.7260         | 0.8171      | 0.7688  |
+| 0.5379        | 4.0   | 6360 | 0.7548          | 0.7210   | 0.6653   | 0.3980        | 0.6354     | 0.4894 | 0.8284           | 0.6635        | 0.7369    | 0.7161         | 0.8320      | 0.7697  |
+| 0.3922        | 5.0   | 7950 | 0.8342          | 0.7323   | 0.6756   | 0.4336        | 0.6084     | 0.5064 | 0.8150           | 0.7024        | 0.7545    | 0.7263         | 0.8099      | 0.7658  |
+
+
+### Framework versions
+
+- Transformers 5.4.0
+- Pytorch 2.11.0+cu130
+- Datasets 4.8.4
+- Tokenizers 0.22.2

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:25f6e69009eadbb31e93040e3f541933333365b0a994a48c68d809eded68e2dd
+oid sha256:b2a64ecdcc50f18808948fe678969167b4172c3c2b0e7c7362e0f45ea0e0e564
 size 409103292

tokenizer_config.json

@@ -0,0 +1,14 @@
+{
+  "backend": "tokenizers",
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "is_local": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}