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Tommert25
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robbert0510_lrate9b16

Token Classification
Transformers
PyTorch
roberta
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +20 -20
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -18,11 +18,11 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.5873
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- - Precisions: 0.8240
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- - Recall: 0.8030
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- - F-measure: 0.8121
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- - Accuracy: 0.9175
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  ## Model description
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@@ -41,7 +41,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 9e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -53,20 +53,20 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
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- | 0.6115 | 1.0 | 236 | 0.3939 | 0.8592 | 0.6769 | 0.6912 | 0.8757 |
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- | 0.3166 | 2.0 | 472 | 0.3750 | 0.7447 | 0.7640 | 0.7458 | 0.8897 |
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- | 0.194 | 3.0 | 708 | 0.3445 | 0.7683 | 0.7462 | 0.7525 | 0.9025 |
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- | 0.1292 | 4.0 | 944 | 0.3776 | 0.8345 | 0.7570 | 0.7754 | 0.9072 |
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- | 0.0755 | 5.0 | 1180 | 0.4667 | 0.7897 | 0.8244 | 0.7995 | 0.9079 |
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- | 0.0556 | 6.0 | 1416 | 0.4879 | 0.8233 | 0.7809 | 0.7973 | 0.9086 |
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- | 0.0413 | 7.0 | 1652 | 0.4901 | 0.7770 | 0.8020 | 0.7846 | 0.9049 |
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- | 0.0245 | 8.0 | 1888 | 0.5467 | 0.8159 | 0.7679 | 0.7836 | 0.9086 |
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- | 0.015 | 9.0 | 2124 | 0.5914 | 0.8156 | 0.7858 | 0.7957 | 0.9109 |
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- | 0.0129 | 10.0 | 2360 | 0.5640 | 0.8041 | 0.8160 | 0.8079 | 0.9133 |
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- | 0.0055 | 11.0 | 2596 | 0.5848 | 0.8084 | 0.8044 | 0.8055 | 0.9142 |
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- | 0.0068 | 12.0 | 2832 | 0.5752 | 0.8097 | 0.7957 | 0.8017 | 0.9140 |
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- | 0.0036 | 13.0 | 3068 | 0.5873 | 0.8240 | 0.8030 | 0.8121 | 0.9175 |
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- | 0.0025 | 14.0 | 3304 | 0.5992 | 0.8217 | 0.7913 | 0.8037 | 0.9155 |
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  ### Framework versions
 
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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: 0.5895
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+ - Precisions: 0.8184
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+ - Recall: 0.7998
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+ - F-measure: 0.8078
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+ - Accuracy: 0.9148
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 8e-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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  | Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
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+ | 0.5957 | 1.0 | 236 | 0.4045 | 0.8529 | 0.6860 | 0.6940 | 0.8784 |
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+ | 0.3024 | 2.0 | 472 | 0.3456 | 0.7564 | 0.7584 | 0.7471 | 0.8964 |
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+ | 0.1843 | 3.0 | 708 | 0.3792 | 0.8188 | 0.7691 | 0.7741 | 0.9087 |
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+ | 0.1163 | 4.0 | 944 | 0.4231 | 0.8317 | 0.7678 | 0.7878 | 0.9060 |
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+ | 0.0753 | 5.0 | 1180 | 0.4595 | 0.8051 | 0.7846 | 0.7911 | 0.9070 |
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+ | 0.0496 | 6.0 | 1416 | 0.4942 | 0.8188 | 0.7803 | 0.7960 | 0.9087 |
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+ | 0.0321 | 7.0 | 1652 | 0.5121 | 0.7966 | 0.7927 | 0.7900 | 0.9103 |
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+ | 0.0246 | 8.0 | 1888 | 0.5057 | 0.8155 | 0.7959 | 0.8030 | 0.9148 |
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+ | 0.0156 | 9.0 | 2124 | 0.5445 | 0.8039 | 0.7924 | 0.7967 | 0.9109 |
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+ | 0.0118 | 10.0 | 2360 | 0.5646 | 0.8151 | 0.7948 | 0.8032 | 0.9140 |
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+ | 0.0083 | 11.0 | 2596 | 0.5911 | 0.8387 | 0.7872 | 0.8075 | 0.9138 |
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+ | 0.0052 | 12.0 | 2832 | 0.5895 | 0.8184 | 0.7998 | 0.8078 | 0.9148 |
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+ | 0.0038 | 13.0 | 3068 | 0.5839 | 0.8193 | 0.7987 | 0.8078 | 0.9149 |
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+ | 0.0026 | 14.0 | 3304 | 0.5911 | 0.8195 | 0.7926 | 0.8041 | 0.9135 |
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  ### Framework versions
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