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diogopaes10
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015-microsoft-deberta-v3-base-finetuned-yahoo-80_20

Text Classification
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deberta-v2
Generated from Trainer
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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: 015-microsoft-deberta-v3-base-finetuned-yahoo-80_20
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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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+ # 015-microsoft-deberta-v3-base-finetuned-yahoo-80_20
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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: 2.0709
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+ - F1: 0.2744
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+ - Accuracy: 0.35
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+ - Precision: 0.2452
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+ - Recall: 0.35
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+ - System Ram Used: 3.9663
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+ - System Ram Total: 83.4807
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+ - Gpu Ram Allocated: 2.0874
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+ - Gpu Ram Cached: 6.8516
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+ - Gpu Ram Total: 39.5640
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+ - Gpu Utilization: 14
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+ - Disk Space Used: 24.7820
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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: 40
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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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+ | 2.3062 | 2.0 | 6 | 2.3028 | 0.025 | 0.1 | 0.0143 | 0.1 | 3.9009 | 83.4807 | 2.0874 | 6.8398 | 39.5640 | 51 | 24.7819 | 78.1898 |
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+ | 2.304 | 4.0 | 12 | 2.3020 | 0.0722 | 0.15 | 0.0625 | 0.15 | 3.9032 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 56 | 24.7819 | 78.1898 |
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+ | 2.2892 | 6.0 | 18 | 2.2997 | 0.0111 | 0.05 | 0.0063 | 0.05 | 3.9136 | 83.4807 | 2.0874 | 6.8418 | 39.5640 | 62 | 24.7819 | 78.1898 |
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+ | 2.2729 | 8.0 | 24 | 2.2947 | 0.0190 | 0.1 | 0.0105 | 0.1 | 3.9411 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 56 | 24.7819 | 78.1898 |
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+ | 2.2108 | 10.0 | 30 | 2.2843 | 0.0521 | 0.15 | 0.0333 | 0.15 | 3.9439 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 60 | 24.7819 | 78.1898 |
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+ | 2.1482 | 12.0 | 36 | 2.2660 | 0.1417 | 0.2 | 0.1643 | 0.2 | 3.9451 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 48 | 24.7819 | 78.1898 |
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+ | 2.0203 | 14.0 | 42 | 2.2328 | 0.2086 | 0.3 | 0.1617 | 0.3 | 3.9597 | 83.4807 | 2.0874 | 6.8418 | 39.5640 | 52 | 24.7819 | 78.1898 |
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+ | 1.8707 | 16.0 | 48 | 2.2030 | 0.2019 | 0.3 | 0.1533 | 0.3 | 3.9691 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 55 | 24.7819 | 78.1898 |
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+ | 1.701 | 18.0 | 54 | 2.1741 | 0.2638 | 0.35 | 0.2483 | 0.35 | 3.9705 | 83.4807 | 2.0873 | 6.8418 | 39.5640 | 58 | 24.7819 | 78.1898 |
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+ | 1.5493 | 20.0 | 60 | 2.1379 | 0.2967 | 0.35 | 0.3 | 0.35 | 3.9699 | 83.4807 | 2.0874 | 6.8516 | 39.5640 | 57 | 24.7819 | 78.1898 |
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+ | 1.4073 | 22.0 | 66 | 2.1232 | 0.2244 | 0.3 | 0.1952 | 0.3 | 3.9711 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 51 | 24.7819 | 78.1898 |
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+ | 1.2447 | 24.0 | 72 | 2.1096 | 0.2344 | 0.3 | 0.2119 | 0.3 | 3.9705 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 49 | 24.7819 | 78.1898 |
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+ | 1.155 | 26.0 | 78 | 2.0978 | 0.3178 | 0.4 | 0.3119 | 0.4 | 3.9663 | 83.4807 | 2.0874 | 6.8516 | 39.5640 | 56 | 24.7819 | 78.1898 |
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+ | 1.0522 | 28.0 | 84 | 2.0805 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9661 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 63 | 24.7820 | 78.1898 |
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+ | 0.9741 | 30.0 | 90 | 2.0735 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9575 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 59 | 24.7820 | 78.1898 |
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+ | 0.9042 | 32.0 | 96 | 2.0793 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9661 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 50 | 24.7820 | 78.1898 |
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+ | 0.8497 | 34.0 | 102 | 2.0769 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9654 | 83.4807 | 2.0874 | 6.8516 | 39.5640 | 58 | 24.7820 | 78.1898 |
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+ | 0.8228 | 36.0 | 108 | 2.0736 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9660 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 60 | 24.7820 | 78.1898 |
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+ | 0.7908 | 38.0 | 114 | 2.0717 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9659 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 59 | 24.7820 | 78.1898 |
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+ | 0.7998 | 40.0 | 120 | 2.0709 | 0.2744 | 0.35 | 0.2452 | 0.35 | 3.9661 | 83.4807 | 2.0873 | 6.8516 | 39.5640 | 59 | 24.7820 | 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