End of training
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README.md
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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_seed35_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_seed35_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: 0.3736
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- Precisions: 0.8703
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- Recall: 0.8320
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- F-measure: 0.8460
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- Accuracy: 0.9455
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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: 35
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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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| 0.4597 | 1.0 | 236 | 0.2601 | 0.8795 | 0.7027 | 0.7178 | 0.9224 |
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| 0.2359 | 2.0 | 472 | 0.2642 | 0.7554 | 0.7436 | 0.7448 | 0.9209 |
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| 0.1425 | 3.0 | 708 | 0.2765 | 0.8100 | 0.7809 | 0.7872 | 0.9318 |
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| 0.0893 | 4.0 | 944 | 0.2727 | 0.8404 | 0.7708 | 0.7885 | 0.9340 |
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| 0.0597 | 5.0 | 1180 | 0.3136 | 0.8572 | 0.7712 | 0.7963 | 0.9361 |
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| 0.0446 | 6.0 | 1416 | 0.3246 | 0.8474 | 0.7824 | 0.7947 | 0.9409 |
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| 0.029 | 7.0 | 1652 | 0.3266 | 0.8266 | 0.7944 | 0.7985 | 0.9361 |
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| 0.0181 | 8.0 | 1888 | 0.3377 | 0.8564 | 0.8139 | 0.8257 | 0.9422 |
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| 0.0152 | 9.0 | 2124 | 0.3578 | 0.8240 | 0.8439 | 0.8297 | 0.9426 |
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| 0.0121 | 10.0 | 2360 | 0.3270 | 0.8659 | 0.8292 | 0.8444 | 0.9475 |
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| 0.0094 | 11.0 | 2596 | 0.3510 | 0.8742 | 0.8274 | 0.8455 | 0.9467 |
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| 0.0057 | 12.0 | 2832 | 0.3674 | 0.8435 | 0.8350 | 0.8379 | 0.9441 |
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| 0.0042 | 13.0 | 3068 | 0.3746 | 0.8708 | 0.8313 | 0.8458 | 0.9458 |
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| 0.0027 | 14.0 | 3304 | 0.3736 | 0.8703 | 0.8320 | 0.8460 | 0.9455 |
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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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runs/Nov14_10-28-29_4376ee55f323/events.out.tfevents.1699958464.4376ee55f323.1225.9
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version https://git-lfs.github.com/spec/v1
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oid sha256:789e8ec5ca2ce1599e7096f601f0b02d452dddc6b007ac925011df353d43aa9a
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size 568
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