Training completed!

README.md

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----
-license: mit
-base_model: xlm-roberta-base
-tags:
-- generated_from_trainer
-metrics:
-- f1
-model-index:
-- name: xlm-roberta-base-finetuned-panx-de
-  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. -->
-
-# xlm-roberta-base-finetuned-panx-de
-
-This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on WikiANN (also called PAN-X), a subset of the Cross-lingual TRansfer Evaluation of Multilingual Encoders.
-It achieves the following results on the evaluation set:
-- Loss: 0.1386
-- F1: 0.8627
-
-### Intended uses & limitations
-
-This model is intended for use in applications requiring named entity recognition in the German language. Example use cases include:
-
-- Automated information extraction from German text sources.
-- Enhancing search engines with entity-aware search capabilities.
-- Assisting in document organization and tagging in multilingual contexts.
-
-**Limitations**:
-- The model is fine-tuned only on German data from the WikiANN dataset. Its performance on other languages or domains may not be as high.
-- It may not perform well on informal or highly specialized text without further fine-tuning.
-
-## Training and evaluation data
-
-The model was fine-tuned on the German subset of the WikiANN (PAN-X) dataset. This dataset is part of the XTREME benchmark and provides annotated named entities in multiple languages, making it suitable for training cross-lingual NER models.
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 24
-- eval_batch_size: 24
-- 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 | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.2544        | 1.0   | 525  | 0.1504          | 0.8230 |
-| 0.1277        | 2.0   | 1050 | 0.1416          | 0.8506 |
-| 0.0796        | 3.0   | 1575 | 0.1386          | 0.8627 |
-
-
-### Framework versions
-
-- Transformers 4.40.2
-- Pytorch 2.3.0+cpu
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+---
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: xlm-roberta-base-finetuned-panx-de
+  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. -->
+
+# xlm-roberta-base-finetuned-panx-de
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1365
+- F1: 0.8694
+
+## 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: 24
+- eval_batch_size: 24
+- 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 | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.2551        | 1.0   | 525  | 0.1531          | 0.8267 |
+| 0.1254        | 2.0   | 1050 | 0.1380          | 0.8555 |
+| 0.0782        | 3.0   | 1575 | 0.1365          | 0.8694 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.3.0+cpu
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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