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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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- 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: movieHunt4-ner |
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results: [] |
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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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# movieHunt4-ner |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0005 |
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- Precision: 1.0 |
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- Recall: 1.0 |
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- F1: 1.0 |
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- Accuracy: 1.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 30 |
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### Training results |
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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 | 48 | 0.0284 | 0.9959 | 0.9959 | 0.9959 | 0.9974 | |
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| No log | 2.0 | 96 | 0.0060 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| No log | 3.0 | 144 | 0.0034 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| No log | 4.0 | 192 | 0.0025 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| No log | 5.0 | 240 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| No log | 6.0 | 288 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| No log | 7.0 | 336 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| No log | 8.0 | 384 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| No log | 9.0 | 432 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| No log | 10.0 | 480 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0168 | 11.0 | 528 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0168 | 12.0 | 576 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0168 | 13.0 | 624 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0168 | 14.0 | 672 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0168 | 15.0 | 720 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0168 | 16.0 | 768 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0168 | 17.0 | 816 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0168 | 18.0 | 864 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0168 | 19.0 | 912 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0168 | 20.0 | 960 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 21.0 | 1008 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 22.0 | 1056 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 23.0 | 1104 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 24.0 | 1152 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 25.0 | 1200 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 26.0 | 1248 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 27.0 | 1296 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 28.0 | 1344 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 29.0 | 1392 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 30.0 | 1440 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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