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End of training

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  1. README.md +69 -0
  2. pytorch_model.bin +1 -1
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: Tommert25/robbert0410_lrate7.5b32
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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: robbert1010_lrate7.5b32
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+ results: []
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+ ---
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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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+
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+ # robbert1010_lrate7.5b32
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+
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+ This model is a fine-tuned version of [Tommert25/robbert0410_lrate7.5b32](https://huggingface.co/Tommert25/robbert0410_lrate7.5b32) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5187
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+ - Precisions: 0.8552
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+ - Recall: 0.7999
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+ - F-measure: 0.8232
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+ - Accuracy: 0.9157
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 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: 6
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
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+ | 0.0496 | 1.0 | 118 | 0.5283 | 0.8488 | 0.7962 | 0.8132 | 0.9092 |
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+ | 0.0474 | 2.0 | 236 | 0.4726 | 0.7961 | 0.7965 | 0.7931 | 0.9075 |
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+ | 0.026 | 3.0 | 354 | 0.5187 | 0.8552 | 0.7999 | 0.8232 | 0.9157 |
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+ | 0.0145 | 4.0 | 472 | 0.5150 | 0.8372 | 0.7791 | 0.7998 | 0.9116 |
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+ | 0.0088 | 5.0 | 590 | 0.5250 | 0.8372 | 0.7818 | 0.8021 | 0.9141 |
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+ | 0.007 | 6.0 | 708 | 0.5299 | 0.8468 | 0.7849 | 0.8072 | 0.9162 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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