End of training

README.md

@@ -0,0 +1,66 @@
+---
+license: mit
+base_model: bert-base-german-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: finetuned-bert-base-german-cased
+  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. -->
+
+# finetuned-bert-base-german-cased
+
+This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4021
+- Accuracy: 0.9076
+- F1: 0.9079
+- Per Class F1: {'Web': 0.973293768545994, 'Panorama': 0.8637681159420288, 'International': 0.9078498293515358, 'Wirtschaft': 0.891304347826087, 'Sport': 0.9916666666666667, 'Inland': 0.825242718446602, 'Etat': 0.9160305343511451, 'Wissenschaft': 0.8717948717948718, 'Kultur': 0.8828828828828829}
+- Per Class Accuracy: {'Web': 0.9704142011834319, 'Panorama': 0.8418079096045198, 'International': 0.9366197183098591, 'Wirtschaft': 0.9111111111111111, 'Sport': 0.9916666666666667, 'Inland': 0.8173076923076923, 'Etat': 0.9375, 'Wissenschaft': 0.85, 'Kultur': 0.8596491228070176}
+
+## 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: 1e-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 | Accuracy | F1     | Per Class F1                                                                                                                                                                                                                                                                                | Per Class Accuracy                                                                                                                                                                                                                                                                         |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| 0.525         | 1.0   | 1156 | 0.3350          | 0.8920   | 0.8919 | {'Web': 0.9583333333333334, 'Panorama': 0.8402366863905326, 'International': 0.8933333333333333, 'Wirtschaft': 0.8741258741258741, 'Sport': 0.9876543209876543, 'Inland': 0.8309178743961353, 'Etat': 0.8617886178861788, 'Wissenschaft': 0.8648648648648649, 'Kultur': 0.8571428571428572} | {'Web': 0.9583333333333334, 'Panorama': 0.8352941176470589, 'International': 0.8993288590604027, 'Wirtschaft': 0.8620689655172413, 'Sport': 0.975609756097561, 'Inland': 0.819047619047619, 'Etat': 0.9464285714285714, 'Wissenschaft': 0.8888888888888888, 'Kultur': 0.8275862068965517}  |
+| 0.3553        | 2.0   | 2312 | 0.3731          | 0.9086   | 0.9090 | {'Web': 0.960960960960961, 'Panorama': 0.8703170028818443, 'International': 0.9041095890410958, 'Wirtschaft': 0.8970588235294118, 'Sport': 0.995850622406639, 'Inland': 0.8396226415094339, 'Etat': 0.9104477611940298, 'Wissenschaft': 0.8793103448275862, 'Kultur': 0.8807339449541284}   | {'Web': 0.9696969696969697, 'Panorama': 0.8435754189944135, 'International': 0.9361702127659575, 'Wirtschaft': 0.9312977099236641, 'Sport': 0.9917355371900827, 'Inland': 0.8090909090909091, 'Etat': 0.9104477611940298, 'Wissenschaft': 0.864406779661017, 'Kultur': 0.8727272727272727} |
+| 0.3083        | 3.0   | 3468 | 0.4021          | 0.9076   | 0.9079 | {'Web': 0.973293768545994, 'Panorama': 0.8637681159420288, 'International': 0.9078498293515358, 'Wirtschaft': 0.891304347826087, 'Sport': 0.9916666666666667, 'Inland': 0.825242718446602, 'Etat': 0.9160305343511451, 'Wissenschaft': 0.8717948717948718, 'Kultur': 0.8828828828828829}    | {'Web': 0.9704142011834319, 'Panorama': 0.8418079096045198, 'International': 0.9366197183098591, 'Wirtschaft': 0.9111111111111111, 'Sport': 0.9916666666666667, 'Inland': 0.8173076923076923, 'Etat': 0.9375, 'Wissenschaft': 0.85, 'Kultur': 0.8596491228070176}                          |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.3.1
+- Datasets 2.19.1
+- Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c0c99cf30f8f676ca00a4ab7cfcbd6f7469b852de57871c041e631c55da74386
+oid sha256:f650af2cabf57cfdeeb778235eb8372e8bbf0b1c68d24627a07919b513aef5d3
 size 436376588