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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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+
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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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+ # funnel-transformer-xlarge_ner_wikiann
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+
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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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+
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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: 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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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