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distilbert-base-uncased-finetuned-text_cl

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: distilbert-base-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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+ - recall
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+ - precision
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+ - f1
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+ model-index:
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+ - name: distilbert-base-uncased-finetuned-text_cl
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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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+ # distilbert-base-uncased-finetuned-text_cl
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2450
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+ - Accuracy: 0.8641
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+ - Recall: 0.9482
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+ - Precision: 0.8402
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+ - F1: 0.8910
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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: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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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 | Recall | Precision | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 231 | 0.4105 | 0.7765 | 0.9343 | 0.7474 | 0.8305 |
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+ | No log | 2.0 | 462 | 0.5147 | 0.7946 | 0.9741 | 0.75 | 0.8475 |
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+ | 0.2425 | 3.0 | 693 | 0.3620 | 0.8407 | 0.9373 | 0.8175 | 0.8733 |
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+ | 0.2425 | 4.0 | 924 | 0.5248 | 0.8646 | 0.9402 | 0.8459 | 0.8906 |
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+ | 0.0988 | 5.0 | 1155 | 0.7085 | 0.8553 | 0.9492 | 0.8287 | 0.8849 |
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+ | 0.0988 | 6.0 | 1386 | 0.7420 | 0.8652 | 0.9084 | 0.8677 | 0.8876 |
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+ | 0.0284 | 7.0 | 1617 | 0.7172 | 0.8705 | 0.9442 | 0.8510 | 0.8952 |
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+ | 0.0284 | 8.0 | 1848 | 0.8150 | 0.8681 | 0.9442 | 0.8479 | 0.8935 |
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+ | 0.0084 | 9.0 | 2079 | 0.9139 | 0.8629 | 0.9373 | 0.8455 | 0.8890 |
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+ | 0.0084 | 10.0 | 2310 | 0.9463 | 0.8571 | 0.9392 | 0.8367 | 0.8850 |
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+ | 0.009 | 11.0 | 2541 | 0.9524 | 0.8658 | 0.9124 | 0.8658 | 0.8885 |
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+ | 0.009 | 12.0 | 2772 | 1.1889 | 0.8483 | 0.9512 | 0.8190 | 0.8802 |
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+ | 0.0036 | 13.0 | 3003 | 1.1781 | 0.8524 | 0.9592 | 0.8196 | 0.8839 |
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+ | 0.0036 | 14.0 | 3234 | 1.1979 | 0.8489 | 0.9572 | 0.8165 | 0.8812 |
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+ | 0.0036 | 15.0 | 3465 | 1.0633 | 0.8635 | 0.9373 | 0.8462 | 0.8894 |
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+ | 0.0064 | 16.0 | 3696 | 1.0781 | 0.8629 | 0.9333 | 0.8480 | 0.8886 |
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+ | 0.0064 | 17.0 | 3927 | 1.1728 | 0.8477 | 0.9452 | 0.8216 | 0.8791 |
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+ | 0.0033 | 18.0 | 4158 | 1.1487 | 0.8536 | 0.9432 | 0.8300 | 0.8830 |
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+ | 0.0033 | 19.0 | 4389 | 1.1052 | 0.8600 | 0.9482 | 0.8351 | 0.8881 |
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+ | 0.0031 | 20.0 | 4620 | 1.1933 | 0.8629 | 0.9612 | 0.8312 | 0.8915 |
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+ | 0.0031 | 21.0 | 4851 | 1.3387 | 0.8454 | 0.9671 | 0.8071 | 0.8799 |
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+ | 0.0029 | 22.0 | 5082 | 1.1393 | 0.8635 | 0.9482 | 0.8395 | 0.8906 |
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+ | 0.0029 | 23.0 | 5313 | 1.2048 | 0.8617 | 0.9522 | 0.8349 | 0.8897 |
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+ | 0.0003 | 24.0 | 5544 | 1.1798 | 0.8652 | 0.9522 | 0.8393 | 0.8922 |
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+ | 0.0003 | 25.0 | 5775 | 1.1385 | 0.8705 | 0.9412 | 0.8529 | 0.8949 |
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+ | 0.0014 | 26.0 | 6006 | 1.2903 | 0.8565 | 0.9532 | 0.8279 | 0.8861 |
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+ | 0.0014 | 27.0 | 6237 | 1.1961 | 0.8635 | 0.9412 | 0.8438 | 0.8898 |
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+ | 0.0014 | 28.0 | 6468 | 1.2178 | 0.8635 | 0.9442 | 0.8419 | 0.8901 |
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+ | 0.0013 | 29.0 | 6699 | 1.2409 | 0.8635 | 0.9472 | 0.8401 | 0.8904 |
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+ | 0.0013 | 30.0 | 6930 | 1.2450 | 0.8641 | 0.9482 | 0.8402 | 0.8910 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.51.3
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.5.0
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+ - Tokenizers 0.21.1
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