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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: distilbert-base-cased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: distilbert-base-cased-logdetective-extraction-retrained
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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-cased-logdetective-extraction-retrained
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+
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+ This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.3047
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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: 8
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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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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 9 | 5.4981 |
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+ | No log | 2.0 | 18 | 4.7485 |
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+ | No log | 3.0 | 27 | 4.2960 |
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+ | No log | 4.0 | 36 | 4.0269 |
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+ | No log | 5.0 | 45 | 3.0733 |
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+ | No log | 6.0 | 54 | 2.9759 |
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+ | No log | 7.0 | 63 | 2.5961 |
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+ | No log | 8.0 | 72 | 2.3365 |
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+ | No log | 9.0 | 81 | 2.4470 |
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+ | No log | 10.0 | 90 | 2.3994 |
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+ | No log | 11.0 | 99 | 2.3914 |
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+ | No log | 12.0 | 108 | 2.3324 |
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+ | No log | 13.0 | 117 | 2.2978 |
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+ | No log | 14.0 | 126 | 2.2797 |
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+ | No log | 15.0 | 135 | 2.2886 |
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+ | No log | 16.0 | 144 | 2.2969 |
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+ | No log | 17.0 | 153 | 2.3091 |
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+ | No log | 18.0 | 162 | 2.2597 |
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+ | No log | 19.0 | 171 | 2.3080 |
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+ | No log | 20.0 | 180 | 2.3047 |
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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 0.15.1
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