End of training
Browse files- README.md +69 -0
- pytorch_model.bin +1 -1
README.md
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---
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base_model: KISTI-AI/scideberta-cs
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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: scideberta-cs-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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# scideberta-cs-ner
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This model is a fine-tuned version of [KISTI-AI/scideberta-cs](https://huggingface.co/KISTI-AI/scideberta-cs) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1552
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- Precision: 0.4943
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- Recall: 0.5475
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- F1: 0.5195
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- Accuracy: 0.9589
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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: 16
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- eval_batch_size: 16
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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: 5
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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 | 60 | 0.1980 | 0.3445 | 0.2723 | 0.3042 | 0.9530 |
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| No log | 2.0 | 120 | 0.1579 | 0.4444 | 0.4358 | 0.4401 | 0.9582 |
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| No log | 3.0 | 180 | 0.1520 | 0.4751 | 0.5321 | 0.5020 | 0.9568 |
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| No log | 4.0 | 240 | 0.1518 | 0.4955 | 0.5433 | 0.5183 | 0.9592 |
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| No log | 5.0 | 300 | 0.1552 | 0.4943 | 0.5475 | 0.5195 | 0.9589 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.1.0+cu121
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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pytorch_model.bin
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