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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: google-bert/bert-base-uncased |
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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: VF_BERT_ST_1800 |
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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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# VF_BERT_ST_1800 |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2457 |
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- Precision: 0.9489 |
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- Recall: 0.9480 |
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- F1: 0.9485 |
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- Accuracy: 0.9405 |
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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: 2e-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: 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 | 30 | 0.4723 | 0.8973 | 0.9212 | 0.9091 | 0.8971 | |
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| No log | 2.0 | 60 | 0.3328 | 0.9146 | 0.9288 | 0.9217 | 0.9076 | |
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| No log | 3.0 | 90 | 0.3022 | 0.9316 | 0.9301 | 0.9308 | 0.9168 | |
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| No log | 4.0 | 120 | 0.2758 | 0.9207 | 0.9398 | 0.9301 | 0.9169 | |
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| No log | 5.0 | 150 | 0.2592 | 0.9392 | 0.9431 | 0.9411 | 0.9322 | |
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| No log | 6.0 | 180 | 0.2586 | 0.9445 | 0.9449 | 0.9447 | 0.9366 | |
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| No log | 7.0 | 210 | 0.2519 | 0.9476 | 0.9447 | 0.9461 | 0.9372 | |
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| No log | 8.0 | 240 | 0.2468 | 0.9464 | 0.9474 | 0.9469 | 0.9394 | |
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| No log | 9.0 | 270 | 0.2475 | 0.9486 | 0.9476 | 0.9481 | 0.9399 | |
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| No log | 10.0 | 300 | 0.2457 | 0.9489 | 0.9480 | 0.9485 | 0.9405 | |
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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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