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  1. README.md +116 -0
  2. adapter_config.json +27 -0
  3. adapter_model.safetensors +3 -0
  4. logs/events.out.tfevents.1709401842.1035aef27825.205.0 +3 -0
  5. logs/events.out.tfevents.1709402144.1035aef27825.205.1 +3 -0
  6. logs/events.out.tfevents.1709402291.1035aef27825.205.2 +3 -0
  7. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: mit
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+ library_name: peft
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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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+ - f1
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+ base_model: MoritzLaurer/mDeBERTa-v3-base-mnli-xnli
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+ model-index:
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+ - name: legal-data-mDeBERTa_V3
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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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+ # legal-data-mDeBERTa_V3
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+
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+ This model is a fine-tuned version of [MoritzLaurer/mDeBERTa-v3-base-mnli-xnli](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6731
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+ - Accuracy: 0.7634
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+ - Precision: 0.7683
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+ - Recall: 0.7644
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+ - F1: 0.7623
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+ - Ratio: 0.3297
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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: 0.005
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+ - train_batch_size: 20
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 40
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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_ratio: 0.06
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+ - lr_scheduler_warmup_steps: 4
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+ - num_epochs: 15
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+ - label_smoothing_factor: 0.1
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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 | F1 | Ratio |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | 1.4203 | 0.34 | 10 | 1.5822 | 0.6022 | 0.6054 | 0.6046 | 0.5997 | 0.3226 |
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+ | 1.1177 | 0.69 | 20 | 0.8339 | 0.7240 | 0.7270 | 0.7253 | 0.7258 | 0.3262 |
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+ | 0.9484 | 1.03 | 30 | 0.7998 | 0.7168 | 0.7610 | 0.7192 | 0.6951 | 0.3190 |
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+ | 0.9257 | 1.38 | 40 | 0.7183 | 0.7204 | 0.7221 | 0.7220 | 0.7219 | 0.3297 |
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+ | 0.9529 | 1.72 | 50 | 0.7397 | 0.6989 | 0.7022 | 0.7001 | 0.6959 | 0.3297 |
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+ | 0.9111 | 2.07 | 60 | 0.6820 | 0.7204 | 0.7215 | 0.7216 | 0.7188 | 0.3333 |
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+ | 0.9021 | 2.41 | 70 | 0.6832 | 0.7563 | 0.7644 | 0.7570 | 0.7509 | 0.3333 |
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+ | 0.8849 | 2.76 | 80 | 0.7858 | 0.7204 | 0.7365 | 0.7227 | 0.7079 | 0.3297 |
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+ | 0.8767 | 3.1 | 90 | 0.8523 | 0.5520 | 0.6258 | 0.5527 | 0.5677 | 0.1935 |
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+ | 0.9186 | 3.45 | 100 | 0.6877 | 0.7276 | 0.7430 | 0.7283 | 0.7183 | 0.3262 |
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+ | 0.9127 | 3.79 | 110 | 0.6426 | 0.7348 | 0.7398 | 0.7357 | 0.7298 | 0.3333 |
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+ | 0.9126 | 4.14 | 120 | 0.7509 | 0.7348 | 0.7564 | 0.7370 | 0.7215 | 0.3297 |
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+ | 0.8477 | 4.48 | 130 | 0.6818 | 0.7491 | 0.7684 | 0.7497 | 0.7406 | 0.3262 |
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+ | 0.8747 | 4.83 | 140 | 0.7813 | 0.6810 | 0.7704 | 0.6842 | 0.6067 | 0.3262 |
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+ | 0.9112 | 5.17 | 150 | 0.7799 | 0.7204 | 0.8141 | 0.7205 | 0.6686 | 0.3297 |
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+ | 0.8767 | 5.52 | 160 | 0.7959 | 0.6989 | 0.8418 | 0.7021 | 0.6271 | 0.3297 |
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+ | 0.863 | 5.86 | 170 | 0.7007 | 0.7240 | 0.7395 | 0.7247 | 0.7139 | 0.3262 |
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+ | 0.9029 | 6.21 | 180 | 0.6524 | 0.7634 | 0.7717 | 0.7642 | 0.7621 | 0.3262 |
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+ | 0.8427 | 6.55 | 190 | 0.7417 | 0.7133 | 0.7374 | 0.7157 | 0.6957 | 0.3262 |
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+ | 0.8945 | 6.9 | 200 | 0.7312 | 0.7527 | 0.7738 | 0.7532 | 0.7437 | 0.3262 |
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+ | 0.8913 | 7.24 | 210 | 0.6410 | 0.7455 | 0.7523 | 0.7473 | 0.7433 | 0.3297 |
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+ | 0.8848 | 7.59 | 220 | 0.7137 | 0.7563 | 0.7585 | 0.7574 | 0.7567 | 0.3297 |
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+ | 0.8553 | 7.93 | 230 | 0.6940 | 0.7599 | 0.7743 | 0.7605 | 0.7530 | 0.3297 |
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+ | 0.8154 | 8.28 | 240 | 0.6460 | 0.7276 | 0.7453 | 0.7298 | 0.7154 | 0.3297 |
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+ | 0.8842 | 8.62 | 250 | 0.7455 | 0.7563 | 0.7694 | 0.7570 | 0.7498 | 0.3297 |
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+ | 0.8773 | 8.97 | 260 | 0.7369 | 0.7348 | 0.7490 | 0.7367 | 0.7291 | 0.3262 |
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+ | 0.8615 | 9.31 | 270 | 0.6577 | 0.7455 | 0.7539 | 0.7464 | 0.7411 | 0.3297 |
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+ | 0.8664 | 9.66 | 280 | 0.6970 | 0.7563 | 0.7631 | 0.7580 | 0.7545 | 0.3297 |
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+ | 0.8855 | 10.0 | 290 | 0.7167 | 0.7204 | 0.7269 | 0.7224 | 0.7169 | 0.3297 |
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+ | 0.8564 | 10.34 | 300 | 0.6808 | 0.7670 | 0.7846 | 0.7676 | 0.7594 | 0.3297 |
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+ | 0.841 | 10.69 | 310 | 0.6604 | 0.7455 | 0.7491 | 0.7472 | 0.7455 | 0.3297 |
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+ | 0.8415 | 11.03 | 320 | 0.7150 | 0.7563 | 0.7694 | 0.7570 | 0.7498 | 0.3297 |
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+ | 0.848 | 11.38 | 330 | 0.6495 | 0.7670 | 0.7685 | 0.7682 | 0.7680 | 0.3297 |
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+ | 0.8648 | 11.72 | 340 | 0.7094 | 0.7348 | 0.7562 | 0.7369 | 0.7245 | 0.3262 |
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+ | 0.8465 | 12.07 | 350 | 0.7125 | 0.7384 | 0.7758 | 0.7387 | 0.7181 | 0.3262 |
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+ | 0.8875 | 12.41 | 360 | 0.6962 | 0.7563 | 0.7590 | 0.7573 | 0.7564 | 0.3297 |
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+ | 0.8192 | 12.76 | 370 | 0.6496 | 0.7455 | 0.7539 | 0.7464 | 0.7411 | 0.3297 |
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+ | 0.8089 | 13.1 | 380 | 0.6569 | 0.7599 | 0.7621 | 0.7613 | 0.7607 | 0.3297 |
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+ | 0.8191 | 13.45 | 390 | 0.6808 | 0.7348 | 0.7679 | 0.7372 | 0.7150 | 0.3297 |
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+ | 0.8468 | 13.79 | 400 | 0.6843 | 0.7670 | 0.7789 | 0.7677 | 0.7621 | 0.3297 |
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+ | 0.8277 | 14.14 | 410 | 0.6630 | 0.7599 | 0.7660 | 0.7607 | 0.7578 | 0.3297 |
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+ | 0.8159 | 14.48 | 420 | 0.6621 | 0.7599 | 0.7650 | 0.7608 | 0.7584 | 0.3297 |
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+ | 0.8803 | 14.83 | 430 | 0.6731 | 0.7634 | 0.7683 | 0.7644 | 0.7623 | 0.3297 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.9.0
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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+ "task_type": "SEQ_CLS",
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+ "use_dora": false,
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+ "use_rslora": false
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