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roberta-large-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-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-2-32-13-30
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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-large-sst-2-32-13-30
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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: 0.8494
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+ - Accuracy: 0.6406
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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 | 0.7123 | 0.5 |
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+ | No log | 2.0 | 4 | 0.7030 | 0.5 |
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+ | No log | 3.0 | 6 | 0.6935 | 0.5 |
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+ | No log | 4.0 | 8 | 0.6906 | 0.5312 |
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+ | 0.718 | 5.0 | 10 | 0.6893 | 0.6094 |
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+ | 0.718 | 6.0 | 12 | 0.6883 | 0.5625 |
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+ | 0.718 | 7.0 | 14 | 0.6860 | 0.5469 |
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+ | 0.718 | 8.0 | 16 | 0.6811 | 0.6094 |
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+ | 0.718 | 9.0 | 18 | 0.6780 | 0.5781 |
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+ | 0.6565 | 10.0 | 20 | 0.6859 | 0.5469 |
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+ | 0.6565 | 11.0 | 22 | 0.6943 | 0.5469 |
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+ | 0.6565 | 12.0 | 24 | 0.7061 | 0.5469 |
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+ | 0.6565 | 13.0 | 26 | 0.6963 | 0.5469 |
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+ | 0.6565 | 14.0 | 28 | 0.7058 | 0.5781 |
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+ | 0.5726 | 15.0 | 30 | 0.7036 | 0.5938 |
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+ | 0.5726 | 16.0 | 32 | 0.7185 | 0.6094 |
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+ | 0.5726 | 17.0 | 34 | 0.7307 | 0.6094 |
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+ | 0.5726 | 18.0 | 36 | 0.7743 | 0.6094 |
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+ | 0.5726 | 19.0 | 38 | 0.7790 | 0.5938 |
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+ | 0.4219 | 20.0 | 40 | 0.7805 | 0.6094 |
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+ | 0.4219 | 21.0 | 42 | 0.7744 | 0.6094 |
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+ | 0.4219 | 22.0 | 44 | 0.7960 | 0.5938 |
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+ | 0.4219 | 23.0 | 46 | 0.8495 | 0.6094 |
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+ | 0.4219 | 24.0 | 48 | 0.8893 | 0.5938 |
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+ | 0.3261 | 25.0 | 50 | 0.8901 | 0.625 |
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+ | 0.3261 | 26.0 | 52 | 0.8924 | 0.625 |
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+ | 0.3261 | 27.0 | 54 | 0.8908 | 0.6094 |
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+ | 0.3261 | 28.0 | 56 | 0.8769 | 0.6094 |
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+ | 0.3261 | 29.0 | 58 | 0.8592 | 0.6094 |
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+ | 0.2415 | 30.0 | 60 | 0.8494 | 0.6406 |
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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