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--- |
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license: apache-2.0 |
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base_model: 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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- accuracy |
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- f1 |
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model-index: |
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- name: bert-base-phia-secondhandDescription-1000 |
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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-base-phia-secondhandDescription-1000 |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9318 |
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- Precision: 0.8414 |
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- Recall: 0.8311 |
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- Accuracy: 0.8311 |
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- F1: 0.8306 |
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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: 10 |
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- eval_batch_size: 10 |
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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 | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:| |
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| No log | 1.0 | 84 | 1.4608 | 0.7781 | 0.6824 | 0.6824 | 0.6766 | |
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| No log | 2.0 | 168 | 0.7149 | 0.8298 | 0.8176 | 0.8176 | 0.8185 | |
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| 1.4174 | 3.0 | 252 | 0.6704 | 0.8229 | 0.8041 | 0.8041 | 0.8036 | |
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| 1.4174 | 4.0 | 336 | 0.8298 | 0.8359 | 0.7973 | 0.7973 | 0.7974 | |
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| 0.2952 | 5.0 | 420 | 0.7800 | 0.8525 | 0.8311 | 0.8311 | 0.8305 | |
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| 0.2952 | 6.0 | 504 | 0.8365 | 0.8464 | 0.8311 | 0.8311 | 0.8312 | |
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| 0.2952 | 7.0 | 588 | 0.9032 | 0.8309 | 0.8176 | 0.8176 | 0.8184 | |
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| 0.0537 | 8.0 | 672 | 0.8952 | 0.8337 | 0.8243 | 0.8243 | 0.8237 | |
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| 0.0537 | 9.0 | 756 | 0.9206 | 0.8414 | 0.8311 | 0.8311 | 0.8306 | |
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| 0.0243 | 10.0 | 840 | 0.9318 | 0.8414 | 0.8311 | 0.8311 | 0.8306 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.1 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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