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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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- recall |
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- accuracy |
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model-index: |
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- name: robbert_seed33_1311 |
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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_seed33_1311 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3569 |
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- Precisions: 0.8341 |
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- Recall: 0.8159 |
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- F-measure: 0.8240 |
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- Accuracy: 0.9424 |
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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: 7.5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 33 |
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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: 14 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:| |
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| 0.4471 | 1.0 | 236 | 0.2653 | 0.7696 | 0.7076 | 0.7131 | 0.9195 | |
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| 0.2264 | 2.0 | 472 | 0.2367 | 0.8184 | 0.7497 | 0.7777 | 0.9279 | |
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| 0.1443 | 3.0 | 708 | 0.2710 | 0.8069 | 0.7735 | 0.7817 | 0.9315 | |
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| 0.0869 | 4.0 | 944 | 0.2697 | 0.8391 | 0.7998 | 0.8150 | 0.9364 | |
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| 0.0531 | 5.0 | 1180 | 0.2877 | 0.8622 | 0.7952 | 0.8178 | 0.9393 | |
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| 0.0373 | 6.0 | 1416 | 0.3171 | 0.8338 | 0.8120 | 0.8204 | 0.9422 | |
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| 0.0238 | 7.0 | 1652 | 0.3312 | 0.8247 | 0.7921 | 0.8047 | 0.9390 | |
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| 0.0159 | 8.0 | 1888 | 0.3569 | 0.8341 | 0.8159 | 0.8240 | 0.9424 | |
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| 0.0122 | 9.0 | 2124 | 0.3832 | 0.8398 | 0.8127 | 0.8238 | 0.9422 | |
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| 0.0058 | 10.0 | 2360 | 0.4160 | 0.8288 | 0.7975 | 0.8098 | 0.9400 | |
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| 0.0059 | 11.0 | 2596 | 0.4153 | 0.8321 | 0.8012 | 0.8124 | 0.9405 | |
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| 0.0045 | 12.0 | 2832 | 0.4399 | 0.8130 | 0.7909 | 0.7994 | 0.9369 | |
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| 0.0024 | 13.0 | 3068 | 0.4357 | 0.8358 | 0.8026 | 0.8163 | 0.9409 | |
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| 0.0035 | 14.0 | 3304 | 0.4391 | 0.8374 | 0.8036 | 0.8175 | 0.9414 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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