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bert-large-uncased-sst-2-16-13-30

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: apache-2.0
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+ base_model: bert-large-uncased
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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: bert-large-uncased-sst-2-16-13-30
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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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+ # bert-large-uncased-sst-2-16-13-30
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+
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+ This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6328
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+ - Accuracy: 0.625
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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 | 1 | 0.7326 | 0.5 |
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+ | No log | 2.0 | 2 | 0.7299 | 0.5 |
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+ | No log | 3.0 | 3 | 0.7258 | 0.5 |
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+ | No log | 4.0 | 4 | 0.7173 | 0.5 |
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+ | No log | 5.0 | 5 | 0.7098 | 0.5 |
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+ | No log | 6.0 | 6 | 0.7019 | 0.4688 |
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+ | No log | 7.0 | 7 | 0.6969 | 0.5 |
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+ | No log | 8.0 | 8 | 0.6889 | 0.5312 |
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+ | No log | 9.0 | 9 | 0.6846 | 0.5625 |
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+ | 0.6763 | 10.0 | 10 | 0.6781 | 0.5625 |
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+ | 0.6763 | 11.0 | 11 | 0.6697 | 0.5938 |
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+ | 0.6763 | 12.0 | 12 | 0.6681 | 0.625 |
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+ | 0.6763 | 13.0 | 13 | 0.6675 | 0.625 |
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+ | 0.6763 | 14.0 | 14 | 0.6668 | 0.625 |
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+ | 0.6763 | 15.0 | 15 | 0.6666 | 0.625 |
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+ | 0.6763 | 16.0 | 16 | 0.6648 | 0.5938 |
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+ | 0.6763 | 17.0 | 17 | 0.6607 | 0.625 |
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+ | 0.6763 | 18.0 | 18 | 0.6589 | 0.6562 |
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+ | 0.6763 | 19.0 | 19 | 0.6564 | 0.6562 |
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+ | 0.4935 | 20.0 | 20 | 0.6533 | 0.6562 |
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+ | 0.4935 | 21.0 | 21 | 0.6502 | 0.6562 |
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+ | 0.4935 | 22.0 | 22 | 0.6472 | 0.5938 |
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+ | 0.4935 | 23.0 | 23 | 0.6445 | 0.5938 |
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+ | 0.4935 | 24.0 | 24 | 0.6418 | 0.5938 |
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+ | 0.4935 | 25.0 | 25 | 0.6391 | 0.5938 |
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+ | 0.4935 | 26.0 | 26 | 0.6370 | 0.5938 |
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+ | 0.4935 | 27.0 | 27 | 0.6353 | 0.5938 |
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+ | 0.4935 | 28.0 | 28 | 0.6341 | 0.625 |
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+ | 0.4935 | 29.0 | 29 | 0.6333 | 0.625 |
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+ | 0.3659 | 30.0 | 30 | 0.6328 | 0.625 |
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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