Model save

README.md

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+---
+license: mit
+base_model: SCUT-DLVCLab/lilt-roberta-en-base
+tags:
+- generated_from_trainer
+model-index:
+- name: lilt-en-funsd
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# lilt-en-funsd
+
+This model is a fine-tuned version of [SCUT-DLVCLab/lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 1.7170
+- eval_ANSWER: {'precision': 0.8775510204081632, 'recall': 0.8947368421052632, 'f1': 0.886060606060606, 'number': 817}
+- eval_HEADER: {'precision': 0.4644808743169399, 'recall': 0.7142857142857143, 'f1': 0.5629139072847683, 'number': 119}
+- eval_QUESTION: {'precision': 0.8934348239771646, 'recall': 0.871866295264624, 'f1': 0.8825187969924814, 'number': 1077}
+- eval_overall_precision: 0.8491
+- eval_overall_recall: 0.8718
+- eval_overall_f1: 0.8603
+- eval_overall_accuracy: 0.7983
+- eval_runtime: 59.4689
+- eval_samples_per_second: 0.841
+- eval_steps_per_second: 0.118
+- epoch: 84.2105
+- step: 1600
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 2500
+- mixed_precision_training: Native AMP
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cpu
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

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