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bert_small_summarized

Text Classification
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bert
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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_summarized
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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_summarized
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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: 2.1652
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+ - Accuracy: 0.82
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+ - Precision: 0.4667
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+ - Recall: 0.2
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+ - F1: 0.2800
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+ - D-index: 1.5200
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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 | 0.4533 | 0.825 | 0.0 | 0.0 | 0.0 | 1.4529 |
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+ | No log | 2.0 | 400 | 0.4694 | 0.825 | 0.0 | 0.0 | 0.0 | 1.4529 |
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+ | 0.5094 | 3.0 | 600 | 0.6237 | 0.825 | 0.0 | 0.0 | 0.0 | 1.4529 |
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+ | 0.5094 | 4.0 | 800 | 0.7898 | 0.81 | 0.4286 | 0.2571 | 0.3214 | 1.5270 |
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+ | 0.3984 | 5.0 | 1000 | 0.9268 | 0.83 | 0.5556 | 0.1429 | 0.2273 | 1.5127 |
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+ | 0.3984 | 6.0 | 1200 | 1.3541 | 0.8 | 0.4074 | 0.3143 | 0.3548 | 1.5339 |
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+ | 0.3984 | 7.0 | 1400 | 1.4264 | 0.805 | 0.375 | 0.1714 | 0.2353 | 1.4893 |
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+ | 0.0939 | 8.0 | 1600 | 1.8870 | 0.8 | 0.4194 | 0.3714 | 0.3939 | 1.5539 |
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+ | 0.0939 | 9.0 | 1800 | 1.8734 | 0.825 | 0.5 | 0.1143 | 0.1860 | 1.4955 |
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+ | 0.0061 | 10.0 | 2000 | 1.8938 | 0.825 | 0.5 | 0.1714 | 0.2553 | 1.5164 |
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+ | 0.0061 | 11.0 | 2200 | 2.0755 | 0.825 | 0.5 | 0.1143 | 0.1860 | 1.4955 |
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+ | 0.0061 | 12.0 | 2400 | 2.1068 | 0.805 | 0.4231 | 0.3143 | 0.3607 | 1.5406 |
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+ | 0.0134 | 13.0 | 2600 | 2.0895 | 0.82 | 0.4444 | 0.1143 | 0.1818 | 1.4887 |
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+ | 0.0134 | 14.0 | 2800 | 2.0520 | 0.815 | 0.4545 | 0.2857 | 0.3509 | 1.5439 |
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+ | 0.0011 | 15.0 | 3000 | 2.0795 | 0.81 | 0.4211 | 0.2286 | 0.2963 | 1.5168 |
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+ | 0.0011 | 16.0 | 3200 | 2.1177 | 0.815 | 0.4444 | 0.2286 | 0.3019 | 1.5235 |
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+ | 0.0011 | 17.0 | 3400 | 2.1396 | 0.815 | 0.4444 | 0.2286 | 0.3019 | 1.5235 |
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+ | 0.0003 | 18.0 | 3600 | 2.1605 | 0.825 | 0.5 | 0.2286 | 0.3137 | 1.5370 |
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+ | 0.0003 | 19.0 | 3800 | 2.1677 | 0.825 | 0.5 | 0.2286 | 0.3137 | 1.5370 |
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+ | 0.0 | 20.0 | 4000 | 2.1652 | 0.82 | 0.4667 | 0.2 | 0.2800 | 1.5200 |
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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