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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: lilt-xlm-roberta-base
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - token-classification
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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: finetuned-v-1
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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: funsd
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+ type: token-classification
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.5977671451355662
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+ - name: Recall
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+ type: recall
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+ value: 0.5977671451355662
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+ - name: F1
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+ type: f1
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+ value: 0.5977671451355662
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.5977671451355662
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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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+ # finetuned-v-1
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+
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+ This model is a fine-tuned version of [lilt-xlm-roberta-base](https://huggingface.co/lilt-xlm-roberta-base) on the funsd dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1752
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+ - Precision: 0.5978
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+ - Recall: 0.5978
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+ - F1: 0.5978
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+ - Accuracy: 0.5978
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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: 8
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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: 1
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+ - mixed_precision_training: Native AMP
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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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+ | 1.3986 | 0.5319 | 100 | 1.1752 | 0.5978 | 0.5978 | 0.5978 | 0.5978 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.2
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+ - Pytorch 2.5.0+cu124
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
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+ "_name_or_path": "nielsr/lilt-xlm-roberta-base",
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+ "LiltForTokenClassification"
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+ ],
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