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bart-large-lora-no-grad

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/bart-large
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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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+ - precision
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+ - recall
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+ model-index:
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+ - name: bart-large-lora-no-grad
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+ results: []
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+ ---
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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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+
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+ # bart-large-lora-no-grad
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+
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+ This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0593
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+ - Accuracy: 0.8366
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+ - Precision: 0.8350
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+ - Recall: 0.8366
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+ - Precision Macro: 0.8149
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+ - Recall Macro: 0.7856
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+ - Macro Fpr: 0.0144
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+ - Weighted Fpr: 0.0138
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+ - Weighted Specificity: 0.9778
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+ - Macro Specificity: 0.9876
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+ - Weighted Sensitivity: 0.8366
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+ - Macro Sensitivity: 0.7856
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+ - F1 Micro: 0.8366
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+ - F1 Macro: 0.7922
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+ - F1 Weighted: 0.8329
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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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: 15
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Precision Macro | Recall Macro | Macro Fpr | Weighted Fpr | Weighted Specificity | Macro Specificity | Weighted Sensitivity | Macro Sensitivity | F1 Micro | F1 Macro | F1 Weighted |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---------------:|:------------:|:---------:|:------------:|:--------------------:|:-----------------:|:--------------------:|:-----------------:|:--------:|:--------:|:-----------:|
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+ | 1.3548 | 1.0 | 643 | 0.7811 | 0.7568 | 0.7272 | 0.7568 | 0.4206 | 0.4734 | 0.0234 | 0.0224 | 0.9682 | 0.9817 | 0.7568 | 0.4734 | 0.7568 | 0.4364 | 0.7359 |
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+ | 0.7738 | 2.0 | 1286 | 0.6572 | 0.7893 | 0.7848 | 0.7893 | 0.6529 | 0.5639 | 0.0196 | 0.0187 | 0.9732 | 0.9842 | 0.7893 | 0.5639 | 0.7893 | 0.5618 | 0.7783 |
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+ | 0.6874 | 3.0 | 1929 | 0.6485 | 0.8009 | 0.7994 | 0.8009 | 0.6224 | 0.6498 | 0.0179 | 0.0174 | 0.9767 | 0.9852 | 0.8009 | 0.6498 | 0.8009 | 0.6248 | 0.7948 |
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+ | 0.502 | 4.0 | 2572 | 0.6912 | 0.8257 | 0.8216 | 0.8257 | 0.7661 | 0.7399 | 0.0158 | 0.0149 | 0.9738 | 0.9866 | 0.8257 | 0.7399 | 0.8257 | 0.7393 | 0.8182 |
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+ | 0.4443 | 5.0 | 3215 | 0.6655 | 0.8350 | 0.8324 | 0.8350 | 0.7584 | 0.7344 | 0.0146 | 0.0139 | 0.9781 | 0.9875 | 0.8350 | 0.7344 | 0.8350 | 0.7352 | 0.8308 |
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+ | 0.3903 | 6.0 | 3858 | 0.7269 | 0.8304 | 0.8288 | 0.8304 | 0.7500 | 0.7407 | 0.0149 | 0.0144 | 0.9789 | 0.9873 | 0.8304 | 0.7407 | 0.8304 | 0.7363 | 0.8261 |
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+ | 0.3398 | 7.0 | 4501 | 0.8292 | 0.8218 | 0.8264 | 0.8218 | 0.8274 | 0.7793 | 0.0161 | 0.0152 | 0.9752 | 0.9865 | 0.8218 | 0.7793 | 0.8218 | 0.7883 | 0.8163 |
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+ | 0.2818 | 8.0 | 5144 | 0.8360 | 0.8218 | 0.8240 | 0.8218 | 0.8251 | 0.7683 | 0.0159 | 0.0152 | 0.9767 | 0.9866 | 0.8218 | 0.7683 | 0.8218 | 0.7744 | 0.8178 |
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+ | 0.2572 | 9.0 | 5787 | 0.8456 | 0.8342 | 0.8328 | 0.8342 | 0.7999 | 0.7735 | 0.0146 | 0.0140 | 0.9787 | 0.9875 | 0.8342 | 0.7735 | 0.8342 | 0.7768 | 0.8310 |
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+ | 0.2594 | 10.0 | 6430 | 0.8724 | 0.8428 | 0.8414 | 0.8428 | 0.8149 | 0.7891 | 0.0138 | 0.0132 | 0.9790 | 0.9881 | 0.8428 | 0.7891 | 0.8428 | 0.7955 | 0.8396 |
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+ | 0.208 | 11.0 | 7073 | 0.9797 | 0.8335 | 0.8339 | 0.8335 | 0.8092 | 0.7870 | 0.0148 | 0.0141 | 0.9774 | 0.9874 | 0.8335 | 0.7870 | 0.8335 | 0.7896 | 0.8303 |
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+ | 0.1786 | 12.0 | 7716 | 1.0180 | 0.8311 | 0.8323 | 0.8311 | 0.8100 | 0.7846 | 0.0149 | 0.0143 | 0.9777 | 0.9873 | 0.8311 | 0.7846 | 0.8311 | 0.7906 | 0.8285 |
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+ | 0.1556 | 13.0 | 8359 | 1.0392 | 0.8358 | 0.8335 | 0.8358 | 0.8040 | 0.7830 | 0.0146 | 0.0138 | 0.9773 | 0.9875 | 0.8358 | 0.7830 | 0.8358 | 0.7876 | 0.8321 |
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+ | 0.1419 | 14.0 | 9002 | 1.0568 | 0.8381 | 0.8362 | 0.8381 | 0.8110 | 0.7855 | 0.0143 | 0.0136 | 0.9779 | 0.9877 | 0.8381 | 0.7855 | 0.8381 | 0.7917 | 0.8349 |
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+ | 0.1251 | 15.0 | 9645 | 1.0593 | 0.8366 | 0.8350 | 0.8366 | 0.8149 | 0.7856 | 0.0144 | 0.0138 | 0.9778 | 0.9876 | 0.8366 | 0.7856 | 0.8366 | 0.7922 | 0.8329 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.15.1
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