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--- |
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license: mit |
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base_model: pdelobelle/robbert-v2-dutch-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: robbert-v2-dutch-base-finetuned-emotion |
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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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# robbert-v2-dutch-base-finetuned-emotion |
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This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3545 |
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- Accuracy: 0.52 |
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- F1: 0.5123 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 50 |
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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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| 1.5586 | 1.0 | 25 | 1.4429 | 0.42 | 0.2485 | |
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| 1.4425 | 2.0 | 50 | 1.3576 | 0.46 | 0.3533 | |
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| 1.2834 | 3.0 | 75 | 1.3207 | 0.5 | 0.4369 | |
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| 1.1051 | 4.0 | 100 | 1.3228 | 0.48 | 0.4217 | |
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| 0.9053 | 5.0 | 125 | 1.3705 | 0.49 | 0.4302 | |
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| 0.7326 | 6.0 | 150 | 1.4522 | 0.53 | 0.5019 | |
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| 0.5724 | 7.0 | 175 | 1.5445 | 0.53 | 0.5064 | |
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| 0.4411 | 8.0 | 200 | 1.6560 | 0.54 | 0.5120 | |
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| 0.3476 | 9.0 | 225 | 1.7233 | 0.51 | 0.4845 | |
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| 0.2324 | 10.0 | 250 | 1.9150 | 0.52 | 0.5056 | |
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| 0.1866 | 11.0 | 275 | 2.0207 | 0.52 | 0.4975 | |
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| 0.165 | 12.0 | 300 | 2.0863 | 0.52 | 0.5094 | |
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| 0.1291 | 13.0 | 325 | 2.1584 | 0.5 | 0.4833 | |
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| 0.0762 | 14.0 | 350 | 2.2296 | 0.55 | 0.5332 | |
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| 0.0577 | 15.0 | 375 | 2.3171 | 0.5 | 0.4986 | |
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| 0.0424 | 16.0 | 400 | 2.4509 | 0.5 | 0.4795 | |
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| 0.0253 | 17.0 | 425 | 2.5444 | 0.49 | 0.4917 | |
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| 0.0191 | 18.0 | 450 | 2.5894 | 0.51 | 0.5031 | |
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| 0.0123 | 19.0 | 475 | 2.7144 | 0.5 | 0.4995 | |
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| 0.01 | 20.0 | 500 | 2.7358 | 0.53 | 0.5231 | |
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| 0.0086 | 21.0 | 525 | 2.8282 | 0.48 | 0.4825 | |
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| 0.0064 | 22.0 | 550 | 2.8421 | 0.52 | 0.5244 | |
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| 0.0059 | 23.0 | 575 | 2.9267 | 0.53 | 0.5200 | |
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| 0.005 | 24.0 | 600 | 2.9568 | 0.52 | 0.5074 | |
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| 0.0044 | 25.0 | 625 | 3.0420 | 0.47 | 0.4755 | |
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| 0.0066 | 26.0 | 650 | 3.0421 | 0.48 | 0.4881 | |
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| 0.0039 | 27.0 | 675 | 3.1039 | 0.51 | 0.4960 | |
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| 0.0033 | 28.0 | 700 | 3.1226 | 0.51 | 0.4955 | |
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| 0.0033 | 29.0 | 725 | 3.1215 | 0.51 | 0.4999 | |
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| 0.003 | 30.0 | 750 | 3.1649 | 0.51 | 0.4980 | |
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| 0.0025 | 31.0 | 775 | 3.1716 | 0.5 | 0.4921 | |
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| 0.0028 | 32.0 | 800 | 3.2371 | 0.5 | 0.4956 | |
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| 0.0028 | 33.0 | 825 | 3.1730 | 0.52 | 0.5154 | |
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| 0.0055 | 34.0 | 850 | 3.1842 | 0.49 | 0.4884 | |
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| 0.0022 | 35.0 | 875 | 3.2324 | 0.51 | 0.4955 | |
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| 0.0023 | 36.0 | 900 | 3.2221 | 0.52 | 0.5089 | |
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| 0.002 | 37.0 | 925 | 3.2756 | 0.51 | 0.4981 | |
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| 0.0021 | 38.0 | 950 | 3.2866 | 0.51 | 0.5010 | |
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| 0.0019 | 39.0 | 975 | 3.2882 | 0.51 | 0.5010 | |
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| 0.0018 | 40.0 | 1000 | 3.2864 | 0.51 | 0.4967 | |
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| 0.0017 | 41.0 | 1025 | 3.3101 | 0.51 | 0.4967 | |
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| 0.0017 | 42.0 | 1050 | 3.3215 | 0.52 | 0.5089 | |
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| 0.0016 | 43.0 | 1075 | 3.3253 | 0.51 | 0.5043 | |
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| 0.0056 | 44.0 | 1100 | 3.3118 | 0.51 | 0.5043 | |
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| 0.0016 | 45.0 | 1125 | 3.3566 | 0.51 | 0.4981 | |
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| 0.0016 | 46.0 | 1150 | 3.3593 | 0.51 | 0.4981 | |
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| 0.0016 | 47.0 | 1175 | 3.3638 | 0.51 | 0.4981 | |
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| 0.0017 | 48.0 | 1200 | 3.3605 | 0.52 | 0.5089 | |
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| 0.0017 | 49.0 | 1225 | 3.3526 | 0.52 | 0.5123 | |
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| 0.0016 | 50.0 | 1250 | 3.3545 | 0.52 | 0.5123 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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