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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- wikiann |
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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: funnel-transformer-xlarge_ner_wikiann |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: wikiann |
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type: wikiann |
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args: en |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8522084990579862 |
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- name: Recall |
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type: recall |
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value: 0.8633535981903011 |
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- name: F1 |
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type: f1 |
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value: 0.8577448467184043 |
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- name: Accuracy |
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type: accuracy |
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value: 0.935805105791199 |
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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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# funnel-transformer-xlarge_ner_wikiann |
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This model is a fine-tuned version of [funnel-transformer/xlarge](https://huggingface.co/funnel-transformer/xlarge) on the wikiann dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4023 |
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- Precision: 0.8522 |
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- Recall: 0.8634 |
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- F1: 0.8577 |
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- Accuracy: 0.9358 |
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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: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: cosine |
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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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| 0.3193 | 1.0 | 5000 | 0.3116 | 0.8239 | 0.8296 | 0.8267 | 0.9260 | |
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| 0.2836 | 2.0 | 10000 | 0.2846 | 0.8446 | 0.8498 | 0.8472 | 0.9325 | |
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| 0.2237 | 3.0 | 15000 | 0.3258 | 0.8427 | 0.8542 | 0.8484 | 0.9332 | |
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| 0.1303 | 4.0 | 20000 | 0.3801 | 0.8531 | 0.8634 | 0.8582 | 0.9362 | |
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| 0.0867 | 5.0 | 25000 | 0.4023 | 0.8522 | 0.8634 | 0.8577 | 0.9358 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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