jgaertner
/

bert-finetuned-ner4invoice

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 ---
-library_name: transformers
-tags: []
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-# Model Card for Model ID
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 ---
+license: apache-2.0
+base_model: bert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-ner4invoice
+  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. -->
+# bert-finetuned-ner4invoice
+This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0257
+- Precision: 0.8861
+- Recall: 0.9859
+- F1: 0.9333
+- Accuracy: 0.9945
+## 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: 2e-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
+- num_epochs: 3
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 14   | 0.0530          | 0.5455    | 0.5070 | 0.5255 | 0.9830   |
+| No log        | 2.0   | 28   | 0.0450          | 0.7654    | 0.8732 | 0.8158 | 0.9822   |
+| No log        | 3.0   | 42   | 0.0257          | 0.8861    | 0.9859 | 0.9333 | 0.9945   |
+### Framework versions
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1