Model save
Browse files- README.md +86 -0
- model.safetensors +1 -1
README.md
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---
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library_name: transformers
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license: mit
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base_model: microsoft/mdeberta-v3-base
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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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model-index:
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- name: QA-mDeBERTa-v3-large-binary
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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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# QA-mDeBERTa-v3-large-binary
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This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3282
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- Accuracy: 0.8585
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- Unsafe Precision: 0.9033
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- Unsafe Recall: 0.8351
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- Unsafe F1: 0.8679
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- Unsafe Fpr: 0.1121
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- Unsafe Aucpr: 0.9532
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- Safe Precision: 0.8111
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- Safe Recall: 0.8879
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- Safe F1: 0.8477
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- Safe Fpr: 0.1649
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- Safe Aucpr: 0.9161
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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: 6e-06
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Unsafe Precision | Unsafe Recall | Unsafe F1 | Unsafe Fpr | Unsafe Aucpr | Safe Precision | Safe Recall | Safe F1 | Safe Fpr | Safe Aucpr |
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|:-------------:|:------:|:-----:|:---------------:|:--------:|:----------------:|:-------------:|:---------:|:----------:|:------------:|:--------------:|:-----------:|:-------:|:--------:|:----------:|
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| 0.3283 | 0.2501 | 2114 | 0.4026 | 0.8181 | 0.9079 | 0.7491 | 0.8209 | 0.0954 | 0.9303 | 0.7418 | 0.9046 | 0.8152 | 0.2509 | 0.8630 |
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| 0.353 | 0.5001 | 4228 | 0.3597 | 0.8432 | 0.8658 | 0.8499 | 0.8578 | 0.1653 | 0.9402 | 0.8159 | 0.8347 | 0.8252 | 0.1501 | 0.8882 |
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| 0.3248 | 0.7502 | 6342 | 0.3476 | 0.8484 | 0.8928 | 0.8268 | 0.8585 | 0.1245 | 0.9450 | 0.8011 | 0.8755 | 0.8367 | 0.1732 | 0.8972 |
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| 0.3591 | 1.0002 | 8456 | 0.3414 | 0.8512 | 0.8822 | 0.8455 | 0.8635 | 0.1416 | 0.9468 | 0.8158 | 0.8584 | 0.8365 | 0.1545 | 0.9011 |
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| 0.3167 | 1.2503 | 10570 | 0.3428 | 0.8537 | 0.8837 | 0.8488 | 0.8659 | 0.1402 | 0.9482 | 0.8192 | 0.8598 | 0.8390 | 0.1512 | 0.9046 |
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| 0.2944 | 1.5004 | 12684 | 0.3422 | 0.8549 | 0.8864 | 0.8480 | 0.8668 | 0.1364 | 0.9491 | 0.8191 | 0.8636 | 0.8408 | 0.1520 | 0.9072 |
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| 0.2875 | 1.7504 | 14798 | 0.3345 | 0.8577 | 0.8800 | 0.8617 | 0.8708 | 0.1474 | 0.9504 | 0.8309 | 0.8526 | 0.8416 | 0.1383 | 0.9101 |
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| 0.346 | 2.0005 | 16912 | 0.3275 | 0.8583 | 0.8899 | 0.8507 | 0.8698 | 0.1321 | 0.9517 | 0.8225 | 0.8679 | 0.8446 | 0.1493 | 0.9122 |
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| 0.3394 | 2.2505 | 19026 | 0.3280 | 0.8579 | 0.8770 | 0.8661 | 0.8715 | 0.1524 | 0.9516 | 0.8346 | 0.8476 | 0.8410 | 0.1339 | 0.9121 |
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| 0.2935 | 2.5006 | 21140 | 0.3269 | 0.8589 | 0.8761 | 0.8693 | 0.8727 | 0.1543 | 0.9522 | 0.8376 | 0.8457 | 0.8417 | 0.1307 | 0.9133 |
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| 0.2999 | 2.7507 | 23254 | 0.3241 | 0.8609 | 0.8855 | 0.8615 | 0.8733 | 0.1398 | 0.9529 | 0.8320 | 0.8602 | 0.8458 | 0.1385 | 0.9143 |
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| 0.3016 | 3.0007 | 25368 | 0.3243 | 0.8608 | 0.8889 | 0.8570 | 0.8727 | 0.1344 | 0.9530 | 0.8283 | 0.8656 | 0.8465 | 0.1430 | 0.9153 |
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| 0.3097 | 3.2508 | 27482 | 0.3271 | 0.8601 | 0.8832 | 0.8628 | 0.8729 | 0.1432 | 0.9525 | 0.8327 | 0.8568 | 0.8446 | 0.1372 | 0.9142 |
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| 0.2794 | 3.5008 | 29596 | 0.3300 | 0.8604 | 0.8942 | 0.8496 | 0.8713 | 0.1261 | 0.9531 | 0.8224 | 0.8739 | 0.8474 | 0.1504 | 0.9156 |
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| 0.3129 | 3.7509 | 31710 | 0.3282 | 0.8585 | 0.9033 | 0.8351 | 0.8679 | 0.1121 | 0.9532 | 0.8111 | 0.8879 | 0.8477 | 0.1649 | 0.9161 |
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### Framework versions
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- Transformers 4.57.3
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- Pytorch 2.7.1+cu118
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- Datasets 4.4.1
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- Tokenizers 0.22.1
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 1115268200
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version https://git-lfs.github.com/spec/v1
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size 1115268200
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