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bert_small

Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
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+ ---
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+ license: apache-2.0
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: bert_small
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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_small
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.4537
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+ - Accuracy: 0.88
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+ - Precision: 0.625
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+ - Recall: 0.3571
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+ - F1: 0.4545
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+ - D-index: 1.6429
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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: 5e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 8
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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: 1600
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+ - num_epochs: 20
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+ - mixed_precision_training: Native AMP
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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 | Precision | Recall | F1 | D-index |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
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+ | No log | 1.0 | 200 | 0.3773 | 0.86 | 0.0 | 0.0 | 0.0 | 1.4803 |
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+ | No log | 2.0 | 400 | 0.4271 | 0.86 | 0.0 | 0.0 | 0.0 | 1.4803 |
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+ | 0.5126 | 3.0 | 600 | 0.4598 | 0.87 | 0.55 | 0.3929 | 0.4583 | 1.6431 |
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+ | 0.5126 | 4.0 | 800 | 0.6620 | 0.865 | 0.52 | 0.4643 | 0.4906 | 1.6624 |
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+ | 0.2953 | 5.0 | 1000 | 0.8149 | 0.855 | 0.4615 | 0.2143 | 0.2927 | 1.5575 |
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+ | 0.2953 | 6.0 | 1200 | 0.7819 | 0.875 | 0.5714 | 0.4286 | 0.4898 | 1.6623 |
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+ | 0.2953 | 7.0 | 1400 | 1.0426 | 0.86 | 0.5 | 0.3571 | 0.4167 | 1.6173 |
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+ | 0.1565 | 8.0 | 1600 | 1.0078 | 0.885 | 0.7273 | 0.2857 | 0.4103 | 1.6231 |
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+ | 0.1565 | 9.0 | 1800 | 1.2939 | 0.865 | 0.6 | 0.1071 | 0.1818 | 1.5294 |
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+ | 0.0643 | 10.0 | 2000 | 1.2661 | 0.88 | 0.6429 | 0.3214 | 0.4286 | 1.6299 |
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+ | 0.0643 | 11.0 | 2200 | 1.3556 | 0.87 | 0.5833 | 0.25 | 0.3500 | 1.5905 |
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+ | 0.0643 | 12.0 | 2400 | 1.2393 | 0.87 | 0.625 | 0.1786 | 0.2778 | 1.5635 |
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+ | 0.0306 | 13.0 | 2600 | 1.3059 | 0.88 | 0.625 | 0.3571 | 0.4545 | 1.6429 |
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+ | 0.0306 | 14.0 | 2800 | 1.3446 | 0.88 | 0.625 | 0.3571 | 0.4545 | 1.6429 |
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+ | 0.0019 | 15.0 | 3000 | 1.3618 | 0.885 | 0.6471 | 0.3929 | 0.4889 | 1.6622 |
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+ | 0.0019 | 16.0 | 3200 | 1.3785 | 0.885 | 0.6471 | 0.3929 | 0.4889 | 1.6622 |
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+ | 0.0019 | 17.0 | 3400 | 1.4361 | 0.88 | 0.625 | 0.3571 | 0.4545 | 1.6429 |
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+ | 0.0098 | 18.0 | 3600 | 1.4466 | 0.88 | 0.625 | 0.3571 | 0.4545 | 1.6429 |
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+ | 0.0098 | 19.0 | 3800 | 1.4518 | 0.88 | 0.625 | 0.3571 | 0.4545 | 1.6429 |
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+ | 0.0 | 20.0 | 4000 | 1.4537 | 0.88 | 0.625 | 0.3571 | 0.4545 | 1.6429 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.28.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3