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009-microsoft-deberta-v3-base-finetuned-yahoo-800_200

Text Classification
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deberta-v2
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+ ---
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+ license: mit
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+ base_model: microsoft/deberta-v3-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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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: 009-microsoft-deberta-v3-base-finetuned-yahoo-800_200
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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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+ # 009-microsoft-deberta-v3-base-finetuned-yahoo-800_200
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1599
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+ - F1: 0.6588
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+ - Accuracy: 0.66
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+ - Precision: 0.6659
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+ - Recall: 0.66
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+ - System Ram Used: 5.0546
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+ - System Ram Total: 83.4807
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+ - Gpu Ram Allocated: 4.1727
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+ - Gpu Ram Cached: 26.7715
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+ - Gpu Ram Total: 39.5640
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+ - Gpu Utilization: 56
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+ - Disk Space Used: 40.6642
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+ - Disk Space Total: 78.1898
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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: 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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+ - 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 | F1 | Accuracy | Precision | Recall | System Ram Used | System Ram Total | Gpu Ram Allocated | Gpu Ram Cached | Gpu Ram Total | Gpu Utilization | Disk Space Used | Disk Space Total |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|:---------------:|:----------------:|:-----------------:|:--------------:|:-------------:|:---------------:|:---------------:|:----------------:|
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+ | 2.3022 | 0.76 | 19 | 2.3012 | 0.0182 | 0.1 | 0.01 | 0.1 | 4.4456 | 83.4807 | 4.1727 | 26.7598 | 39.5640 | 45 | 33.7570 | 78.1898 |
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+ | 2.2979 | 1.52 | 38 | 2.2854 | 0.0635 | 0.155 | 0.0449 | 0.155 | 5.0347 | 83.4807 | 4.1727 | 26.7715 | 39.5640 | 43 | 38.5922 | 78.1898 |
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+ | 2.2316 | 2.28 | 57 | 2.1098 | 0.2285 | 0.305 | 0.2806 | 0.305 | 5.1781 | 83.4807 | 4.1727 | 26.7715 | 39.5640 | 44 | 40.6639 | 78.1898 |
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+ | 1.9915 | 3.04 | 76 | 1.8477 | 0.4148 | 0.43 | 0.5040 | 0.43 | 5.1741 | 83.4807 | 4.1727 | 26.7715 | 39.5640 | 50 | 40.6639 | 78.1898 |
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+ | 1.684 | 3.8 | 95 | 1.6027 | 0.5272 | 0.55 | 0.5666 | 0.55 | 5.1766 | 83.4807 | 4.1728 | 26.7715 | 39.5640 | 47 | 40.6639 | 78.1898 |
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+ | 1.3911 | 4.56 | 114 | 1.4365 | 0.6060 | 0.615 | 0.6199 | 0.615 | 5.1746 | 83.4807 | 4.1728 | 26.7715 | 39.5640 | 49 | 40.6640 | 78.1898 |
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+ | 1.1477 | 5.32 | 133 | 1.2565 | 0.6215 | 0.615 | 0.6419 | 0.615 | 5.1586 | 83.4807 | 4.1728 | 26.7715 | 39.5640 | 52 | 40.6640 | 78.1898 |
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+ | 0.9198 | 6.08 | 152 | 1.1759 | 0.6400 | 0.64 | 0.6532 | 0.64 | 5.1810 | 83.4807 | 4.1727 | 26.7715 | 39.5640 | 55 | 40.6640 | 78.1898 |
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+ | 0.7605 | 6.84 | 171 | 1.1128 | 0.6418 | 0.645 | 0.6564 | 0.645 | 5.1415 | 83.4807 | 4.1727 | 26.7715 | 39.5640 | 45 | 40.6640 | 78.1898 |
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+ | 0.6093 | 7.6 | 190 | 1.0767 | 0.6678 | 0.67 | 0.6758 | 0.67 | 5.1347 | 83.4807 | 4.1728 | 26.7715 | 39.5640 | 43 | 40.6640 | 78.1898 |
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+ | 0.5111 | 8.36 | 209 | 1.1033 | 0.6552 | 0.655 | 0.6742 | 0.655 | 5.1206 | 83.4807 | 4.1728 | 26.7715 | 39.5640 | 52 | 40.6641 | 78.1898 |
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+ | 0.3828 | 9.12 | 228 | 1.1063 | 0.6875 | 0.69 | 0.6927 | 0.69 | 5.1484 | 83.4807 | 4.1727 | 26.7715 | 39.5640 | 44 | 40.6641 | 78.1898 |
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+ | 0.3082 | 9.88 | 247 | 1.1240 | 0.6573 | 0.665 | 0.6595 | 0.665 | 5.1437 | 83.4807 | 4.1728 | 26.7715 | 39.5640 | 45 | 40.6641 | 78.1898 |
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+ | 0.2716 | 10.64 | 266 | 1.1572 | 0.6604 | 0.665 | 0.6665 | 0.665 | 5.0689 | 83.4807 | 4.1728 | 26.7715 | 39.5640 | 45 | 40.6641 | 78.1898 |
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+ | 0.2442 | 11.4 | 285 | 1.1058 | 0.6765 | 0.675 | 0.6827 | 0.675 | 5.0316 | 83.4807 | 4.1728 | 26.7715 | 39.5640 | 42 | 40.6641 | 78.1898 |
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+ | 0.1791 | 12.16 | 304 | 1.1455 | 0.6445 | 0.645 | 0.6515 | 0.645 | 5.0715 | 83.4807 | 4.1728 | 26.7715 | 39.5640 | 46 | 40.6641 | 78.1898 |
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+ | 0.1604 | 12.92 | 323 | 1.1514 | 0.6578 | 0.66 | 0.6686 | 0.66 | 5.0728 | 83.4807 | 4.1728 | 26.7715 | 39.5640 | 57 | 40.6641 | 78.1898 |
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+ | 0.1389 | 13.68 | 342 | 1.1600 | 0.6715 | 0.675 | 0.6808 | 0.675 | 5.0655 | 83.4807 | 4.1727 | 26.7715 | 39.5640 | 48 | 40.6642 | 78.1898 |
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+ | 0.151 | 14.44 | 361 | 1.1573 | 0.6626 | 0.665 | 0.6687 | 0.665 | 5.0588 | 83.4807 | 4.1727 | 26.7715 | 39.5640 | 48 | 40.6642 | 78.1898 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.13.1
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+ - Tokenizers 0.13.3