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pos_tagger_3112_v3

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  1. README.md +115 -0
  2. model.safetensors +1 -1
  3. runs/Dec31_13-08-20_2fd172ee26d9/events.out.tfevents.1704028100.2fd172ee26d9.3672.0 +2 -2
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: dbmdz/bert-base-turkish-cased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: pos_tagger_3112_v3
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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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+ # pos_tagger_3112_v3
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+
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+ This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7728
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+ - Precision: 0.8922
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+ - Recall: 0.8955
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+ - F1: 0.8938
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+ - Accuracy: 0.9244
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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: 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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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 244 | 0.3040 | 0.8905 | 0.8924 | 0.8915 | 0.9215 |
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+ | No log | 2.0 | 488 | 0.2915 | 0.8981 | 0.9006 | 0.8994 | 0.9279 |
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+ | 0.3896 | 3.0 | 732 | 0.3109 | 0.8933 | 0.8932 | 0.8933 | 0.9234 |
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+ | 0.3896 | 4.0 | 976 | 0.3004 | 0.8954 | 0.8983 | 0.8969 | 0.9263 |
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+ | 0.159 | 5.0 | 1220 | 0.3338 | 0.8929 | 0.8946 | 0.8937 | 0.9242 |
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+ | 0.159 | 6.0 | 1464 | 0.3419 | 0.8914 | 0.8958 | 0.8936 | 0.9240 |
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+ | 0.1038 | 7.0 | 1708 | 0.3840 | 0.8892 | 0.8930 | 0.8911 | 0.9223 |
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+ | 0.1038 | 8.0 | 1952 | 0.3923 | 0.8857 | 0.8930 | 0.8894 | 0.9213 |
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+ | 0.0629 | 9.0 | 2196 | 0.4441 | 0.8888 | 0.8914 | 0.8901 | 0.9213 |
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+ | 0.0629 | 10.0 | 2440 | 0.4769 | 0.8886 | 0.8929 | 0.8908 | 0.9231 |
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+ | 0.0357 | 11.0 | 2684 | 0.4846 | 0.8859 | 0.8913 | 0.8886 | 0.9199 |
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+ | 0.0357 | 12.0 | 2928 | 0.5256 | 0.8877 | 0.8895 | 0.8886 | 0.9211 |
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+ | 0.0212 | 13.0 | 3172 | 0.5554 | 0.8896 | 0.8900 | 0.8898 | 0.9219 |
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+ | 0.0212 | 14.0 | 3416 | 0.5748 | 0.8870 | 0.8911 | 0.8890 | 0.9207 |
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+ | 0.0143 | 15.0 | 3660 | 0.5988 | 0.8877 | 0.8916 | 0.8896 | 0.9220 |
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+ | 0.0143 | 16.0 | 3904 | 0.6047 | 0.8874 | 0.8903 | 0.8888 | 0.9209 |
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+ | 0.0098 | 17.0 | 4148 | 0.6161 | 0.8846 | 0.8914 | 0.8880 | 0.9199 |
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+ | 0.0098 | 18.0 | 4392 | 0.6158 | 0.8883 | 0.8929 | 0.8906 | 0.9217 |
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+ | 0.0072 | 19.0 | 4636 | 0.6216 | 0.8858 | 0.8928 | 0.8893 | 0.9209 |
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+ | 0.0072 | 20.0 | 4880 | 0.6497 | 0.8892 | 0.8926 | 0.8909 | 0.9215 |
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+ | 0.0058 | 21.0 | 5124 | 0.6698 | 0.8887 | 0.8919 | 0.8903 | 0.9216 |
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+ | 0.0058 | 22.0 | 5368 | 0.6582 | 0.8858 | 0.8916 | 0.8887 | 0.9208 |
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+ | 0.0046 | 23.0 | 5612 | 0.6915 | 0.8866 | 0.8925 | 0.8896 | 0.9212 |
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+ | 0.0046 | 24.0 | 5856 | 0.6725 | 0.8898 | 0.8928 | 0.8913 | 0.9222 |
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+ | 0.004 | 25.0 | 6100 | 0.6678 | 0.8912 | 0.8961 | 0.8936 | 0.9238 |
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+ | 0.004 | 26.0 | 6344 | 0.6899 | 0.8891 | 0.8933 | 0.8912 | 0.9224 |
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+ | 0.0034 | 27.0 | 6588 | 0.7082 | 0.8890 | 0.8922 | 0.8906 | 0.9215 |
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+ | 0.0034 | 28.0 | 6832 | 0.7066 | 0.8903 | 0.8920 | 0.8911 | 0.9228 |
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+ | 0.0026 | 29.0 | 7076 | 0.7243 | 0.8882 | 0.8938 | 0.8910 | 0.9228 |
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+ | 0.0026 | 30.0 | 7320 | 0.7322 | 0.8891 | 0.8923 | 0.8907 | 0.9226 |
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+ | 0.0023 | 31.0 | 7564 | 0.7292 | 0.8909 | 0.8930 | 0.8920 | 0.9230 |
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+ | 0.0023 | 32.0 | 7808 | 0.7227 | 0.8922 | 0.8947 | 0.8934 | 0.9244 |
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+ | 0.0027 | 33.0 | 8052 | 0.7231 | 0.8885 | 0.8922 | 0.8903 | 0.9222 |
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+ | 0.0027 | 34.0 | 8296 | 0.7236 | 0.8907 | 0.8936 | 0.8922 | 0.9233 |
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+ | 0.0019 | 35.0 | 8540 | 0.7313 | 0.8875 | 0.8895 | 0.8885 | 0.9214 |
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+ | 0.0019 | 36.0 | 8784 | 0.7240 | 0.8902 | 0.8935 | 0.8919 | 0.9234 |
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+ | 0.0017 | 37.0 | 9028 | 0.7364 | 0.8903 | 0.8939 | 0.8921 | 0.9233 |
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+ | 0.0017 | 38.0 | 9272 | 0.7479 | 0.8896 | 0.8929 | 0.8913 | 0.9232 |
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+ | 0.0013 | 39.0 | 9516 | 0.7511 | 0.8895 | 0.8937 | 0.8916 | 0.9230 |
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+ | 0.0013 | 40.0 | 9760 | 0.7689 | 0.8896 | 0.8948 | 0.8922 | 0.9234 |
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+ | 0.001 | 41.0 | 10004 | 0.7597 | 0.8909 | 0.8958 | 0.8933 | 0.9238 |
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+ | 0.001 | 42.0 | 10248 | 0.7581 | 0.8897 | 0.8929 | 0.8913 | 0.9230 |
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+ | 0.001 | 43.0 | 10492 | 0.7512 | 0.8919 | 0.8952 | 0.8935 | 0.9244 |
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+ | 0.0012 | 44.0 | 10736 | 0.7622 | 0.8921 | 0.8957 | 0.8939 | 0.9244 |
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+ | 0.0012 | 45.0 | 10980 | 0.7707 | 0.8907 | 0.8952 | 0.8930 | 0.9237 |
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+ | 0.001 | 46.0 | 11224 | 0.7700 | 0.8922 | 0.8963 | 0.8942 | 0.9244 |
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+ | 0.001 | 47.0 | 11468 | 0.7742 | 0.8895 | 0.8938 | 0.8916 | 0.9231 |
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+ | 0.0009 | 48.0 | 11712 | 0.7753 | 0.8911 | 0.8945 | 0.8928 | 0.9239 |
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+ | 0.0009 | 49.0 | 11956 | 0.7746 | 0.8909 | 0.8944 | 0.8927 | 0.9236 |
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+ | 0.0008 | 50.0 | 12200 | 0.7728 | 0.8922 | 0.8955 | 0.8938 | 0.9244 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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