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roberta-large-sst-2-64-13-30

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-large
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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-large-sst-2-64-13-30
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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-large-sst-2-64-13-30
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+
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+ This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8764
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+ - Accuracy: 0.8828
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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 | 4 | 0.7179 | 0.5 |
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+ | No log | 2.0 | 8 | 0.6981 | 0.5312 |
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+ | 0.717 | 3.0 | 12 | 0.6948 | 0.4688 |
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+ | 0.717 | 4.0 | 16 | 0.7043 | 0.4453 |
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+ | 0.6986 | 5.0 | 20 | 0.6971 | 0.4688 |
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+ | 0.6986 | 6.0 | 24 | 0.7705 | 0.5156 |
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+ | 0.6986 | 7.0 | 28 | 0.7463 | 0.625 |
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+ | 0.6087 | 8.0 | 32 | 0.7016 | 0.6172 |
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+ | 0.6087 | 9.0 | 36 | 0.5869 | 0.7656 |
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+ | 0.5365 | 10.0 | 40 | 0.5156 | 0.8047 |
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+ | 0.5365 | 11.0 | 44 | 0.4578 | 0.8203 |
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+ | 0.5365 | 12.0 | 48 | 0.3511 | 0.9141 |
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+ | 0.3599 | 13.0 | 52 | 0.3583 | 0.8828 |
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+ | 0.3599 | 14.0 | 56 | 0.3759 | 0.8828 |
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+ | 0.1271 | 15.0 | 60 | 0.4324 | 0.8906 |
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+ | 0.1271 | 16.0 | 64 | 0.4806 | 0.8984 |
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+ | 0.1271 | 17.0 | 68 | 0.5256 | 0.875 |
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+ | 0.0516 | 18.0 | 72 | 0.6432 | 0.8906 |
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+ | 0.0516 | 19.0 | 76 | 0.6976 | 0.875 |
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+ | 0.0034 | 20.0 | 80 | 0.8148 | 0.875 |
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+ | 0.0034 | 21.0 | 84 | 0.8401 | 0.8828 |
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+ | 0.0034 | 22.0 | 88 | 0.8721 | 0.8828 |
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+ | 0.0467 | 23.0 | 92 | 0.8001 | 0.8906 |
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+ | 0.0467 | 24.0 | 96 | 0.8580 | 0.8828 |
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+ | 0.0005 | 25.0 | 100 | 0.8849 | 0.875 |
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+ | 0.0005 | 26.0 | 104 | 0.9024 | 0.875 |
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+ | 0.0005 | 27.0 | 108 | 0.9125 | 0.875 |
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+ | 0.0005 | 28.0 | 112 | 0.8686 | 0.8828 |
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+ | 0.0005 | 29.0 | 116 | 0.8764 | 0.8828 |
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+ | 0.0231 | 30.0 | 120 | 0.8764 | 0.8828 |
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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