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roberta-base-sst-2-32-13-30

Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: mit
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+ base_model: roberta-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: roberta-base-sst-2-32-13-30
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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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+ # roberta-base-sst-2-32-13-30
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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: 0.5496
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+ - Accuracy: 0.75
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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: 1.5e-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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+ - lr_scheduler_warmup_steps: 5
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+ - num_epochs: 30
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 2 | 0.6930 | 0.5156 |
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+ | No log | 2.0 | 4 | 0.6929 | 0.5 |
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+ | No log | 3.0 | 6 | 0.6928 | 0.5 |
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+ | No log | 4.0 | 8 | 0.6925 | 0.5 |
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+ | 0.6955 | 5.0 | 10 | 0.6920 | 0.5 |
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+ | 0.6955 | 6.0 | 12 | 0.6914 | 0.5156 |
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+ | 0.6955 | 7.0 | 14 | 0.6904 | 0.5469 |
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+ | 0.6955 | 8.0 | 16 | 0.6891 | 0.5312 |
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+ | 0.6955 | 9.0 | 18 | 0.6872 | 0.5156 |
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+ | 0.6791 | 10.0 | 20 | 0.6845 | 0.5312 |
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+ | 0.6791 | 11.0 | 22 | 0.6805 | 0.5312 |
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+ | 0.6791 | 12.0 | 24 | 0.6751 | 0.5312 |
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+ | 0.6791 | 13.0 | 26 | 0.6654 | 0.5625 |
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+ | 0.6791 | 14.0 | 28 | 0.6525 | 0.625 |
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+ | 0.6052 | 15.0 | 30 | 0.6347 | 0.6406 |
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+ | 0.6052 | 16.0 | 32 | 0.6130 | 0.6719 |
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+ | 0.6052 | 17.0 | 34 | 0.5903 | 0.6875 |
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+ | 0.6052 | 18.0 | 36 | 0.5770 | 0.6875 |
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+ | 0.6052 | 19.0 | 38 | 0.5569 | 0.7031 |
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+ | 0.3501 | 20.0 | 40 | 0.5333 | 0.75 |
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+ | 0.3501 | 21.0 | 42 | 0.5251 | 0.7344 |
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+ | 0.3501 | 22.0 | 44 | 0.5137 | 0.75 |
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+ | 0.3501 | 23.0 | 46 | 0.5118 | 0.7656 |
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+ | 0.3501 | 24.0 | 48 | 0.5151 | 0.7656 |
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+ | 0.137 | 25.0 | 50 | 0.5202 | 0.7656 |
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+ | 0.137 | 26.0 | 52 | 0.5299 | 0.7656 |
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+ | 0.137 | 27.0 | 54 | 0.5379 | 0.7656 |
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+ | 0.137 | 28.0 | 56 | 0.5433 | 0.75 |
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+ | 0.137 | 29.0 | 58 | 0.5477 | 0.75 |
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+ | 0.0715 | 30.0 | 60 | 0.5496 | 0.75 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.0.dev0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.4.0
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+ - Tokenizers 0.13.3