End of training

README.md

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+---
+license: mit
+base_model: bert-base-german-cased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: Misinformation-Covid-LowLearningRatebert-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. -->
+
+# Misinformation-Covid-LowLearningRatebert-base-german-cased
+
+This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5151
+- F1: 0.3793
+
+## 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-07
+- 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: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.6534        | 1.0   | 189  | 0.6298          | 0.1000 |
+| 0.6467        | 2.0   | 378  | 0.6222          | 0.1379 |
+| 0.6302        | 3.0   | 567  | 0.6121          | 0.0784 |
+| 0.6259        | 4.0   | 756  | 0.6042          | 0.0870 |
+| 0.6255        | 5.0   | 945  | 0.5987          | 0.0870 |
+| 0.6091        | 6.0   | 1134 | 0.5922          | 0.0909 |
+| 0.6237        | 7.0   | 1323 | 0.5881          | 0.1224 |
+| 0.6019        | 8.0   | 1512 | 0.5826          | 0.1277 |
+| 0.6038        | 9.0   | 1701 | 0.5779          | 0.2    |
+| 0.5996        | 10.0  | 1890 | 0.5730          | 0.1961 |
+| 0.5858        | 11.0  | 2079 | 0.5678          | 0.2353 |
+| 0.5794        | 12.0  | 2268 | 0.5636          | 0.24   |
+| 0.5806        | 13.0  | 2457 | 0.5587          | 0.2264 |
+| 0.5586        | 14.0  | 2646 | 0.5548          | 0.24   |
+| 0.5682        | 15.0  | 2835 | 0.5514          | 0.24   |
+| 0.5631        | 16.0  | 3024 | 0.5471          | 0.2353 |
+| 0.5603        | 17.0  | 3213 | 0.5425          | 0.2593 |
+| 0.5437        | 18.0  | 3402 | 0.5393          | 0.2593 |
+| 0.5439        | 19.0  | 3591 | 0.5368          | 0.2642 |
+| 0.547         | 20.0  | 3780 | 0.5329          | 0.2909 |
+| 0.5408        | 21.0  | 3969 | 0.5297          | 0.3158 |
+| 0.5327        | 22.0  | 4158 | 0.5270          | 0.3158 |
+| 0.5194        | 23.0  | 4347 | 0.5256          | 0.3214 |
+| 0.5206        | 24.0  | 4536 | 0.5227          | 0.3214 |
+| 0.516         | 25.0  | 4725 | 0.5205          | 0.3214 |
+| 0.5103        | 26.0  | 4914 | 0.5191          | 0.3214 |
+| 0.5037        | 27.0  | 5103 | 0.5172          | 0.3214 |
+| 0.4974        | 28.0  | 5292 | 0.5180          | 0.3214 |
+| 0.5116        | 29.0  | 5481 | 0.5156          | 0.3214 |
+| 0.5006        | 30.0  | 5670 | 0.5150          | 0.3214 |
+| 0.509         | 31.0  | 5859 | 0.5141          | 0.3214 |
+| 0.4832        | 32.0  | 6048 | 0.5150          | 0.3273 |
+| 0.4877        | 33.0  | 6237 | 0.5133          | 0.3214 |
+| 0.49          | 34.0  | 6426 | 0.5131          | 0.3158 |
+| 0.4827        | 35.0  | 6615 | 0.5143          | 0.3214 |
+| 0.4986        | 36.0  | 6804 | 0.5125          | 0.3214 |
+| 0.4794        | 37.0  | 6993 | 0.5131          | 0.3793 |
+| 0.4809        | 38.0  | 7182 | 0.5137          | 0.3793 |
+| 0.4929        | 39.0  | 7371 | 0.5114          | 0.3793 |
+| 0.465         | 40.0  | 7560 | 0.5135          | 0.3793 |
+| 0.4867        | 41.0  | 7749 | 0.5121          | 0.3793 |
+| 0.4685        | 42.0  | 7938 | 0.5129          | 0.3793 |
+| 0.4643        | 43.0  | 8127 | 0.5142          | 0.3793 |
+| 0.4804        | 44.0  | 8316 | 0.5144          | 0.3793 |
+| 0.4779        | 45.0  | 8505 | 0.5141          | 0.3793 |
+| 0.4701        | 46.0  | 8694 | 0.5139          | 0.3793 |
+| 0.4619        | 47.0  | 8883 | 0.5146          | 0.3793 |
+| 0.4558        | 48.0  | 9072 | 0.5151          | 0.3793 |
+| 0.4824        | 49.0  | 9261 | 0.5152          | 0.3793 |
+| 0.4758        | 50.0  | 9450 | 0.5151          | 0.3793 |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.2
+- Datasets 2.12.0
+- Tokenizers 0.13.3

config.json

@@ -0,0 +1,33 @@
+{
+  "_name_or_path": "bert-base-german-cased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "No misinformation",
+    "1": "Potential misinformation"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "No misinformation": 0,
+    "Potential misinformation": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30000
+}

pytorch_model.bin

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+size 436400366

special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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