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xlm-roberta-large-TASTESet-ner

Token Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: mit
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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: xlm-roberta-large-TASTESet-ner
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+ results: []
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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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+ # xlm-roberta-large-TASTESet-ner
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+
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+ This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4970
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+ - Precision: 0.8662
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+ - Recall: 0.8989
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+ - F1: 0.8822
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+ - Accuracy: 0.8889
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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: 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: 20
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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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+ | No log | 1.0 | 31 | 1.8592 | 0.3077 | 0.4305 | 0.3589 | 0.4376 |
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+ | No log | 2.0 | 62 | 1.3188 | 0.4793 | 0.5445 | 0.5098 | 0.5884 |
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+ | No log | 3.0 | 93 | 1.1581 | 0.5382 | 0.6134 | 0.5733 | 0.6391 |
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+ | No log | 4.0 | 124 | 1.1373 | 0.6480 | 0.5964 | 0.6211 | 0.6522 |
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+ | No log | 5.0 | 155 | 0.8784 | 0.6969 | 0.7370 | 0.7164 | 0.7425 |
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+ | No log | 6.0 | 186 | 0.7242 | 0.7472 | 0.7823 | 0.7643 | 0.7930 |
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+ | No log | 7.0 | 217 | 0.6340 | 0.7869 | 0.8258 | 0.8058 | 0.8225 |
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+ | No log | 8.0 | 248 | 0.5766 | 0.7832 | 0.8562 | 0.8180 | 0.8391 |
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+ | No log | 9.0 | 279 | 0.5200 | 0.8087 | 0.8702 | 0.8383 | 0.8583 |
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+ | No log | 10.0 | 310 | 0.4981 | 0.8495 | 0.8722 | 0.8607 | 0.8642 |
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+ | No log | 11.0 | 341 | 0.4732 | 0.8510 | 0.8836 | 0.8670 | 0.8762 |
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+ | No log | 12.0 | 372 | 0.4884 | 0.8593 | 0.8801 | 0.8696 | 0.8746 |
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+ | No log | 13.0 | 403 | 0.4701 | 0.8444 | 0.8893 | 0.8663 | 0.8825 |
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+ | No log | 14.0 | 434 | 0.4759 | 0.8576 | 0.8898 | 0.8734 | 0.8814 |
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+ | No log | 15.0 | 465 | 0.4765 | 0.8596 | 0.8945 | 0.8767 | 0.8840 |
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+ | No log | 16.0 | 496 | 0.4817 | 0.8610 | 0.8984 | 0.8793 | 0.8881 |
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+ | 0.7221 | 17.0 | 527 | 0.4904 | 0.8572 | 0.8989 | 0.8775 | 0.8869 |
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+ | 0.7221 | 18.0 | 558 | 0.4971 | 0.8640 | 0.8969 | 0.8802 | 0.8869 |
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+ | 0.7221 | 19.0 | 589 | 0.4954 | 0.8595 | 0.9024 | 0.8804 | 0.8894 |
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+ | 0.7221 | 20.0 | 620 | 0.4970 | 0.8662 | 0.8989 | 0.8822 | 0.8889 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.0
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+ - Pytorch 1.13.1+cu117
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+ - Datasets 2.9.0
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+ - Tokenizers 0.13.2