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016-microsoft-MiniLM-finetuned-yahoo-80_20

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+ ---
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+ license: mit
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+ base_model: microsoft/MiniLM-L12-H384-uncased
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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: 016-microsoft-MiniLM-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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+ # 016-microsoft-MiniLM-finetuned-yahoo-80_20
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+
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+ This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6861
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+ - F1: 0.4657
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+ - Accuracy: 0.5
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+ - Precision: 0.5267
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+ - Recall: 0.5
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+ - System Ram Used: 3.8760
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+ - System Ram Total: 83.4807
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+ - Gpu Ram Allocated: 0.3991
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+ - Gpu Ram Cached: 1.9316
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+ - Gpu Ram Total: 39.5640
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+ - Gpu Utilization: 35
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+ - Disk Space Used: 24.5397
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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: 100
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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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+ | 2.3016 | 5.0 | 15 | 2.3016 | 0.0182 | 0.1 | 0.01 | 0.1 | 3.8589 | 83.4807 | 0.3990 | 1.9219 | 39.5640 | 38 | 24.5396 | 78.1898 |
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+ | 2.2944 | 10.0 | 30 | 2.2979 | 0.0182 | 0.1 | 0.01 | 0.1 | 3.8753 | 83.4807 | 0.3991 | 1.9219 | 39.5640 | 36 | 24.5396 | 78.1898 |
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+ | 2.2693 | 15.0 | 45 | 2.2696 | 0.2030 | 0.25 | 0.2472 | 0.25 | 3.8814 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 35 | 24.5396 | 78.1898 |
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+ | 2.1627 | 20.0 | 60 | 2.2004 | 0.1808 | 0.25 | 0.1932 | 0.25 | 3.8785 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 39 | 24.5396 | 78.1898 |
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+ | 1.9951 | 25.0 | 75 | 2.0773 | 0.2649 | 0.35 | 0.2922 | 0.35 | 3.8796 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 38 | 24.5396 | 78.1898 |
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+ | 1.8128 | 30.0 | 90 | 1.9729 | 0.3619 | 0.45 | 0.3533 | 0.45 | 3.8802 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 36 | 24.5396 | 78.1898 |
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+ | 1.6805 | 35.0 | 105 | 1.9061 | 0.4405 | 0.5 | 0.465 | 0.5 | 3.8803 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 37 | 24.5396 | 78.1898 |
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+ | 1.5773 | 40.0 | 120 | 1.8512 | 0.3824 | 0.45 | 0.3767 | 0.45 | 3.8846 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 38 | 24.5396 | 78.1898 |
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+ | 1.4916 | 45.0 | 135 | 1.8222 | 0.5190 | 0.55 | 0.5600 | 0.55 | 3.8846 | 83.4807 | 0.3991 | 1.9316 | 39.5640 | 40 | 24.5397 | 78.1898 |
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+ | 1.4142 | 50.0 | 150 | 1.8056 | 0.4657 | 0.5 | 0.5267 | 0.5 | 3.8850 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 38 | 24.5397 | 78.1898 |
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+ | 1.3555 | 55.0 | 165 | 1.7700 | 0.4657 | 0.5 | 0.5267 | 0.5 | 3.8850 | 83.4807 | 0.3991 | 1.9316 | 39.5640 | 41 | 24.5397 | 78.1898 |
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+ | 1.3029 | 60.0 | 180 | 1.7568 | 0.4657 | 0.5 | 0.5267 | 0.5 | 3.8795 | 83.4807 | 0.3991 | 1.9316 | 39.5640 | 35 | 24.5397 | 78.1898 |
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+ | 1.2572 | 65.0 | 195 | 1.7462 | 0.4371 | 0.45 | 0.5067 | 0.45 | 3.8802 | 83.4807 | 0.3991 | 1.9316 | 39.5640 | 40 | 24.5397 | 78.1898 |
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+ | 1.2207 | 70.0 | 210 | 1.7215 | 0.4371 | 0.45 | 0.5067 | 0.45 | 3.8880 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 37 | 24.5397 | 78.1898 |
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+ | 1.1915 | 75.0 | 225 | 1.7103 | 0.4657 | 0.5 | 0.5267 | 0.5 | 3.8760 | 83.4807 | 0.3991 | 1.9316 | 39.5640 | 39 | 24.5397 | 78.1898 |
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+ | 1.1649 | 80.0 | 240 | 1.7069 | 0.4371 | 0.45 | 0.5067 | 0.45 | 3.8761 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 40 | 24.5397 | 78.1898 |
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+ | 1.1484 | 85.0 | 255 | 1.6911 | 0.4657 | 0.5 | 0.5267 | 0.5 | 3.8747 | 83.4807 | 0.3991 | 1.9316 | 39.5640 | 35 | 24.5397 | 78.1898 |
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+ | 1.135 | 90.0 | 270 | 1.6888 | 0.4657 | 0.5 | 0.5267 | 0.5 | 3.8753 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 37 | 24.5397 | 78.1898 |
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+ | 1.1226 | 95.0 | 285 | 1.6860 | 0.4657 | 0.5 | 0.5267 | 0.5 | 3.8755 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 39 | 24.5397 | 78.1898 |
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+ | 1.1217 | 100.0 | 300 | 1.6861 | 0.4657 | 0.5 | 0.5267 | 0.5 | 3.8755 | 83.4807 | 0.3990 | 1.9316 | 39.5640 | 38 | 24.5397 | 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