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roberta-base-sst-2-32-13-smoothed

Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
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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-smoothed
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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-smoothed
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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: 0.6023
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+ - Accuracy: 0.8906
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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: 1e-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: 50
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+ - num_epochs: 75
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+ - label_smoothing_factor: 0.45
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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 | 0.6943 | 0.5 |
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+ | No log | 2.0 | 4 | 0.6942 | 0.5 |
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+ | No log | 3.0 | 6 | 0.6941 | 0.5 |
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+ | No log | 4.0 | 8 | 0.6939 | 0.5 |
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+ | 0.695 | 5.0 | 10 | 0.6937 | 0.5 |
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+ | 0.695 | 6.0 | 12 | 0.6935 | 0.5 |
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+ | 0.695 | 7.0 | 14 | 0.6933 | 0.5 |
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+ | 0.695 | 8.0 | 16 | 0.6932 | 0.5 |
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+ | 0.695 | 9.0 | 18 | 0.6930 | 0.5 |
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+ | 0.6959 | 10.0 | 20 | 0.6928 | 0.5 |
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+ | 0.6959 | 11.0 | 22 | 0.6927 | 0.5156 |
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+ | 0.6959 | 12.0 | 24 | 0.6926 | 0.6094 |
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+ | 0.6959 | 13.0 | 26 | 0.6925 | 0.5781 |
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+ | 0.6959 | 14.0 | 28 | 0.6923 | 0.5625 |
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+ | 0.6919 | 15.0 | 30 | 0.6922 | 0.5625 |
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+ | 0.6919 | 16.0 | 32 | 0.6920 | 0.5625 |
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+ | 0.6919 | 17.0 | 34 | 0.6917 | 0.6094 |
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+ | 0.6919 | 18.0 | 36 | 0.6913 | 0.5938 |
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+ | 0.6919 | 19.0 | 38 | 0.6908 | 0.6406 |
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+ | 0.6896 | 20.0 | 40 | 0.6902 | 0.7188 |
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+ | 0.6896 | 21.0 | 42 | 0.6892 | 0.7812 |
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+ | 0.6896 | 22.0 | 44 | 0.6878 | 0.6719 |
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+ | 0.6896 | 23.0 | 46 | 0.6855 | 0.7344 |
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+ | 0.6896 | 24.0 | 48 | 0.6816 | 0.7344 |
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+ | 0.6745 | 25.0 | 50 | 0.6737 | 0.7812 |
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+ | 0.6745 | 26.0 | 52 | 0.6571 | 0.8438 |
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+ | 0.6745 | 27.0 | 54 | 0.6290 | 0.8438 |
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+ | 0.6745 | 28.0 | 56 | 0.6161 | 0.8438 |
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+ | 0.6745 | 29.0 | 58 | 0.6202 | 0.8594 |
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+ | 0.5833 | 30.0 | 60 | 0.6190 | 0.875 |
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+ | 0.5833 | 31.0 | 62 | 0.6210 | 0.8594 |
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+ | 0.5833 | 32.0 | 64 | 0.6147 | 0.8594 |
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+ | 0.5833 | 33.0 | 66 | 0.6056 | 0.9062 |
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+ | 0.5833 | 34.0 | 68 | 0.6082 | 0.9062 |
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+ | 0.5433 | 35.0 | 70 | 0.6194 | 0.875 |
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+ | 0.5433 | 36.0 | 72 | 0.6035 | 0.9062 |
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+ | 0.5433 | 37.0 | 74 | 0.5986 | 0.8906 |
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+ | 0.5433 | 38.0 | 76 | 0.5970 | 0.8906 |
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+ | 0.5433 | 39.0 | 78 | 0.6038 | 0.8906 |
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+ | 0.5402 | 40.0 | 80 | 0.6061 | 0.8906 |
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+ | 0.5402 | 41.0 | 82 | 0.6018 | 0.8906 |
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+ | 0.5402 | 42.0 | 84 | 0.6013 | 0.9062 |
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+ | 0.5402 | 43.0 | 86 | 0.6018 | 0.8906 |
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+ | 0.5402 | 44.0 | 88 | 0.6086 | 0.8594 |
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+ | 0.5384 | 45.0 | 90 | 0.6100 | 0.8594 |
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+ | 0.5384 | 46.0 | 92 | 0.6044 | 0.8906 |
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+ | 0.5384 | 47.0 | 94 | 0.6022 | 0.8906 |
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+ | 0.5384 | 48.0 | 96 | 0.6007 | 0.8906 |
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+ | 0.5384 | 49.0 | 98 | 0.6003 | 0.8906 |
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+ | 0.5368 | 50.0 | 100 | 0.6013 | 0.8906 |
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+ | 0.5368 | 51.0 | 102 | 0.6012 | 0.8906 |
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+ | 0.5368 | 52.0 | 104 | 0.6006 | 0.8906 |
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+ | 0.5368 | 53.0 | 106 | 0.6005 | 0.8906 |
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+ | 0.5368 | 54.0 | 108 | 0.6011 | 0.8906 |
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+ | 0.537 | 55.0 | 110 | 0.6013 | 0.8906 |
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+ | 0.537 | 56.0 | 112 | 0.6014 | 0.8906 |
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+ | 0.537 | 57.0 | 114 | 0.6013 | 0.9062 |
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+ | 0.537 | 58.0 | 116 | 0.6011 | 0.9062 |
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+ | 0.537 | 59.0 | 118 | 0.6006 | 0.9062 |
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+ | 0.5364 | 60.0 | 120 | 0.5999 | 0.9062 |
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+ | 0.5364 | 61.0 | 122 | 0.5994 | 0.9062 |
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+ | 0.5364 | 62.0 | 124 | 0.5991 | 0.9062 |
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+ | 0.5364 | 63.0 | 126 | 0.5992 | 0.9062 |
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+ | 0.5364 | 64.0 | 128 | 0.5996 | 0.9062 |
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+ | 0.5362 | 65.0 | 130 | 0.6000 | 0.9062 |
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+ | 0.5362 | 66.0 | 132 | 0.6004 | 0.9062 |
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+ | 0.5362 | 67.0 | 134 | 0.6007 | 0.9062 |
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+ | 0.5362 | 68.0 | 136 | 0.6015 | 0.9062 |
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+ | 0.5362 | 69.0 | 138 | 0.6020 | 0.9062 |
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+ | 0.5362 | 70.0 | 140 | 0.6020 | 0.9062 |
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+ | 0.5362 | 71.0 | 142 | 0.6021 | 0.9062 |
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+ | 0.5362 | 72.0 | 144 | 0.6023 | 0.8906 |
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+ | 0.5362 | 73.0 | 146 | 0.6023 | 0.8906 |
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+ | 0.5362 | 74.0 | 148 | 0.6023 | 0.8906 |
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+ | 0.536 | 75.0 | 150 | 0.6023 | 0.8906 |
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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