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---
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library_name: transformers
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license: apache-2.0
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base_model: bert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: DHBW-T3INF4333-Aufgabe-2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# DHBW-T3INF4333-Aufgabe-2
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3164
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- Accuracy: 0.9204
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- F1: 0.8615
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.4043 | 1.0 | 569 | 0.2547 | 0.9099 | 0.8399 |
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| 0.1911 | 2.0 | 1138 | 0.2272 | 0.9235 | 0.8555 |
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| 0.0569 | 3.0 | 1707 | 0.3164 | 0.9204 | 0.8615 |
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### Framework versions
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- Transformers 4.47.1
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- Pytorch 2.5.1+cu118
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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