Nonzerophilip
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Training complete
Browse files- README.md +0 -20
- config.json +17 -17
- pytorch_model.bin +1 -1
- training_args.bin +1 -1
README.md
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base_model: KBLab/bert-base-swedish-cased-ner
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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: testThesis
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results: []
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# testThesis
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This model is a fine-tuned version of [KBLab/bert-base-swedish-cased-ner](https://huggingface.co/KBLab/bert-base-swedish-cased-ner) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1703
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- Precision: 0.44
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- Recall: 0.2366
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- F1: 0.3077
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- Accuracy: 0.9494
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 3
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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 | 15 | 0.2260 | 0.0385 | 0.0215 | 0.0276 | 0.9343 |
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| No log | 2.0 | 30 | 0.1824 | 0.4444 | 0.2151 | 0.2899 | 0.9476 |
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| No log | 3.0 | 45 | 0.1703 | 0.44 | 0.2366 | 0.3077 | 0.9494 |
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### Framework versions
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- Transformers 4.33.0
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base_model: KBLab/bert-base-swedish-cased-ner
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tags:
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- generated_from_trainer
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model-index:
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- name: testThesis
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results: []
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# testThesis
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This model is a fine-tuned version of [KBLab/bert-base-swedish-cased-ner](https://huggingface.co/KBLab/bert-base-swedish-cased-ner) on an unknown dataset.
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Framework versions
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- Transformers 4.33.0
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config.json
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"hidden_size": 768,
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"id2label": {
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"0": "O",
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"1": "
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"2": "
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"3": "
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"4": "
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"5": "
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"6": "
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"7": "
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"8": "
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"hidden_size": 768,
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"id2label": {
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"0": "O",
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"1": "SMP",
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"2": "PRS",
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"3": "GRO",
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"4": "MNT",
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"5": "WRK",
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"6": "LOC",
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"7": "EVN",
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"8": "TME"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"EVN": "7",
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"GRO": "3",
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"LOC": "6",
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"MNT": "4",
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"O": "0",
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"PRS": "2",
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"SMP": "1",
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"TME": "8",
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"WRK": "5"
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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pytorch_model.bin
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training_args.bin
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