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--- |
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license: mit |
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base_model: deepset/gbert-base |
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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: gecco-german-counseling-gbert-base |
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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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# gecco-german-counseling-gbert-base |
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This model is a fine-tuned version of [deepset/gbert-base](https://huggingface.co/deepset/gbert-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2480 |
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- Accuracy: 0.7194 |
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- F1: 0.5062 |
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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: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 16 |
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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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| 3.439 | 1.0 | 20 | 3.1181 | 0.2484 | 0.0474 | |
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| 2.9431 | 2.0 | 40 | 2.6841 | 0.3935 | 0.1637 | |
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| 2.5477 | 3.0 | 60 | 2.3120 | 0.5387 | 0.2802 | |
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| 2.1823 | 4.0 | 80 | 2.0526 | 0.5935 | 0.3138 | |
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| 1.8786 | 5.0 | 100 | 1.8242 | 0.6387 | 0.3541 | |
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| 1.6267 | 6.0 | 120 | 1.6720 | 0.6548 | 0.3682 | |
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| 1.4447 | 7.0 | 140 | 1.5538 | 0.6645 | 0.3718 | |
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| 1.2734 | 8.0 | 160 | 1.4655 | 0.6710 | 0.3801 | |
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| 1.1099 | 9.0 | 180 | 1.4040 | 0.6935 | 0.4202 | |
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| 1.0766 | 10.0 | 200 | 1.3541 | 0.6903 | 0.4330 | |
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| 0.913 | 11.0 | 220 | 1.3078 | 0.6968 | 0.4629 | |
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| 0.8557 | 12.0 | 240 | 1.2879 | 0.7161 | 0.5000 | |
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| 0.8477 | 13.0 | 260 | 1.2772 | 0.7097 | 0.4946 | |
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| 0.7412 | 14.0 | 280 | 1.2598 | 0.7161 | 0.5042 | |
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| 0.7341 | 15.0 | 300 | 1.2484 | 0.7194 | 0.5069 | |
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| 0.7029 | 16.0 | 320 | 1.2480 | 0.7194 | 0.5062 | |
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### Framework versions |
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- Transformers 4.35.1 |
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- Pytorch 1.10.1+cu111 |
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- Datasets 2.14.7 |
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- Tokenizers 0.14.1 |
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