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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: junior_agent |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# junior_agent |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5637 |
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- Topology Accuracy: 0.8431 |
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- Service Accuracy: 0.9082 |
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- Combined Accuracy: 0.8757 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-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: 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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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Topology Accuracy | Service Accuracy | Combined Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:----------------:|:-----------------:| |
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| 0.8918 | 1.0 | 143 | 0.8370 | 0.7367 | 0.5824 | 0.6596 | |
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| 0.7634 | 2.0 | 286 | 0.6906 | 0.7872 | 0.8045 | 0.7959 | |
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| 0.6648 | 3.0 | 429 | 0.5570 | 0.8351 | 0.8896 | 0.8624 | |
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| 0.4889 | 4.0 | 572 | 0.5268 | 0.8351 | 0.9109 | 0.8730 | |
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| 0.4557 | 5.0 | 715 | 0.5296 | 0.8378 | 0.9109 | 0.8743 | |
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| 0.4257 | 6.0 | 858 | 0.5382 | 0.8364 | 0.9189 | 0.8777 | |
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| 0.4398 | 7.0 | 1001 | 0.5383 | 0.8497 | 0.9215 | 0.8856 | |
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| 0.3671 | 8.0 | 1144 | 0.5535 | 0.8497 | 0.9176 | 0.8836 | |
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| 0.3781 | 9.0 | 1287 | 0.5637 | 0.8431 | 0.9082 | 0.8757 | |
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### Framework versions |
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- Transformers 4.56.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.0 |
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