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roberta-base-ours-run-2

Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
text-embeddings-inference
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+ ---
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+ license: mit
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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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+ model-index:
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+ - name: run-2
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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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+ # run-2
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.1449
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+ - Accuracy: 0.75
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+ - Precision: 0.7115
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+ - Recall: 0.7093
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+ - F1: 0.7103
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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: 5e-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: 20
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.9838 | 1.0 | 50 | 0.8621 | 0.645 | 0.6536 | 0.6130 | 0.6124 |
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+ | 0.7134 | 2.0 | 100 | 0.8124 | 0.7 | 0.6628 | 0.6421 | 0.6483 |
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+ | 0.4911 | 3.0 | 150 | 0.8571 | 0.7 | 0.6726 | 0.6314 | 0.6361 |
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+ | 0.3104 | 4.0 | 200 | 0.8228 | 0.76 | 0.7298 | 0.7367 | 0.7294 |
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+ | 0.1942 | 5.0 | 250 | 1.1132 | 0.76 | 0.7282 | 0.7031 | 0.7119 |
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+ | 0.1409 | 6.0 | 300 | 1.2218 | 0.685 | 0.6516 | 0.6560 | 0.6524 |
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+ | 0.0976 | 7.0 | 350 | 1.3648 | 0.715 | 0.6984 | 0.7044 | 0.6946 |
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+ | 0.0791 | 8.0 | 400 | 1.5985 | 0.745 | 0.7183 | 0.7113 | 0.7124 |
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+ | 0.0647 | 9.0 | 450 | 1.8884 | 0.725 | 0.6818 | 0.6761 | 0.6785 |
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+ | 0.0275 | 10.0 | 500 | 1.8639 | 0.725 | 0.6979 | 0.7008 | 0.6958 |
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+ | 0.0329 | 11.0 | 550 | 1.8831 | 0.72 | 0.6816 | 0.6869 | 0.6838 |
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+ | 0.0169 | 12.0 | 600 | 2.1426 | 0.73 | 0.6864 | 0.6776 | 0.6794 |
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+ | 0.0072 | 13.0 | 650 | 2.2483 | 0.725 | 0.7187 | 0.7054 | 0.6968 |
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+ | 0.0203 | 14.0 | 700 | 2.2901 | 0.735 | 0.6986 | 0.6885 | 0.6921 |
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+ | 0.0093 | 15.0 | 750 | 2.3134 | 0.725 | 0.6830 | 0.6666 | 0.6723 |
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+ | 0.0089 | 16.0 | 800 | 2.1598 | 0.73 | 0.6919 | 0.6860 | 0.6885 |
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+ | 0.0061 | 17.0 | 850 | 2.0879 | 0.75 | 0.7129 | 0.7132 | 0.7125 |
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+ | 0.0024 | 18.0 | 900 | 2.1285 | 0.745 | 0.7062 | 0.7071 | 0.7049 |
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+ | 0.0043 | 19.0 | 950 | 2.1386 | 0.74 | 0.7001 | 0.7003 | 0.6985 |
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+ | 0.0028 | 20.0 | 1000 | 2.1449 | 0.75 | 0.7115 | 0.7093 | 0.7103 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.25.1
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+ - Pytorch 1.13.1+cu116
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+ - Tokenizers 0.13.2