Model save
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README.md
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---
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library_name: transformers
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: bert-clf-biencoder-focal_loss
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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-clf-biencoder-focal_loss
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1151
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- Accuracy: 0.6699
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- F1: 0.6704
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- Precision: 0.6743
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- Recall: 0.6699
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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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- lr_scheduler_warmup_steps: 100
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- num_epochs: 7
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.1474 | 1.0 | 78 | 0.1310 | 0.5631 | 0.5696 | 0.6139 | 0.5631 |
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| 0.1003 | 2.0 | 156 | 0.1011 | 0.6472 | 0.6435 | 0.6673 | 0.6472 |
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| 0.0718 | 3.0 | 234 | 0.0976 | 0.6990 | 0.6996 | 0.7027 | 0.6990 |
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| 0.0513 | 4.0 | 312 | 0.1033 | 0.6731 | 0.6762 | 0.6962 | 0.6731 |
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| 0.0296 | 5.0 | 390 | 0.1072 | 0.6699 | 0.6681 | 0.6702 | 0.6699 |
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| 0.0236 | 6.0 | 468 | 0.1122 | 0.6926 | 0.6928 | 0.6939 | 0.6926 |
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| 0.0156 | 7.0 | 546 | 0.1151 | 0.6699 | 0.6704 | 0.6743 | 0.6699 |
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### Framework versions
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- Transformers 4.45.1
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- Pytorch 2.4.0
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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model.safetensors
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