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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: bert-large-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: bert-large-cased-topic_classification |
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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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# bert-large-cased-topic_classification |
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This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6996 |
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- Precision: 0.9000 |
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- Recall: 0.8902 |
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- F1: 0.8941 |
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- Accuracy: 0.8922 |
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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: 8 |
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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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 44 | 0.6240 | 0.8483 | 0.8532 | 0.8411 | 0.8480 | |
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| No log | 2.0 | 88 | 0.3887 | 0.9054 | 0.8660 | 0.8792 | 0.8873 | |
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| No log | 3.0 | 132 | 0.4416 | 0.9015 | 0.9034 | 0.9022 | 0.9020 | |
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| No log | 4.0 | 176 | 0.6620 | 0.9290 | 0.8847 | 0.8991 | 0.9020 | |
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| No log | 5.0 | 220 | 0.6337 | 0.9148 | 0.8880 | 0.8970 | 0.8971 | |
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| No log | 6.0 | 264 | 0.6673 | 0.8965 | 0.8875 | 0.8905 | 0.8922 | |
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| No log | 7.0 | 308 | 0.6857 | 0.9000 | 0.8902 | 0.8941 | 0.8922 | |
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| No log | 8.0 | 352 | 0.6921 | 0.9000 | 0.8902 | 0.8941 | 0.8922 | |
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| No log | 9.0 | 396 | 0.6976 | 0.9000 | 0.8902 | 0.8941 | 0.8922 | |
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| No log | 10.0 | 440 | 0.6996 | 0.9000 | 0.8902 | 0.8941 | 0.8922 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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