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--- |
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base_model: KennethEnevoldsen/dfm-sentence-encoder-large-exp2-no-lang-align |
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library_name: transformers |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: dfm |
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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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# dfm |
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This model is a fine-tuned version of [KennethEnevoldsen/dfm-sentence-encoder-large-exp2-no-lang-align](https://huggingface.co/KennethEnevoldsen/dfm-sentence-encoder-large-exp2-no-lang-align) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Accuracy: 0.9421 |
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- Precision: 0.9470 |
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- Recall: 0.9421 |
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- F1: 0.9422 |
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- Loss: 0.5839 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 20 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Precision | Recall | F1 | Validation Loss | |
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|:-------------:|:-------:|:----:|:--------:|:---------:|:------:|:------:|:---------------:| |
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| No log | 0.9412 | 8 | 0.8711 | 0.8341 | 0.8711 | 0.8507 | 0.4719 | |
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| No log | 2.0 | 17 | 0.9237 | 0.9242 | 0.9237 | 0.9217 | 0.3301 | |
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| No log | 2.9412 | 25 | 0.9225 | 0.9301 | 0.9225 | 0.9232 | 0.3470 | |
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| No log | 4.0 | 34 | 0.9317 | 0.9315 | 0.9317 | 0.9299 | 0.2004 | |
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| No log | 4.9412 | 42 | 0.9379 | 0.9443 | 0.9379 | 0.9383 | 0.4529 | |
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| No log | 6.0 | 51 | 0.9394 | 0.9454 | 0.9394 | 0.9399 | 0.4719 | |
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| No log | 6.9412 | 59 | 0.9425 | 0.9458 | 0.9425 | 0.9419 | 0.4498 | |
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| No log | 8.0 | 68 | 0.9421 | 0.9471 | 0.9421 | 0.9423 | 0.4921 | |
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| No log | 8.9412 | 76 | 0.9440 | 0.9486 | 0.9440 | 0.9440 | 0.5242 | |
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| No log | 10.0 | 85 | 0.9444 | 0.9488 | 0.9444 | 0.9443 | 0.5476 | |
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| No log | 10.9412 | 93 | 0.9421 | 0.9471 | 0.9421 | 0.9422 | 0.5733 | |
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| No log | 12.0 | 102 | 0.9432 | 0.9479 | 0.9432 | 0.9433 | 0.5725 | |
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| No log | 12.9412 | 110 | 0.9432 | 0.9478 | 0.9432 | 0.9432 | 0.5677 | |
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| No log | 14.0 | 119 | 0.9432 | 0.9478 | 0.9432 | 0.9432 | 0.5714 | |
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| No log | 14.9412 | 127 | 0.9425 | 0.9473 | 0.9425 | 0.9425 | 0.5802 | |
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| No log | 16.0 | 136 | 0.9417 | 0.9468 | 0.9417 | 0.9418 | 0.5838 | |
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| No log | 16.9412 | 144 | 0.9421 | 0.9470 | 0.9421 | 0.9422 | 0.5857 | |
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| No log | 18.0 | 153 | 0.9421 | 0.9470 | 0.9421 | 0.9422 | 0.5840 | |
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| No log | 18.8235 | 160 | 0.9421 | 0.9470 | 0.9421 | 0.9422 | 0.5839 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.19.1 |
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