End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-multilingual-uncased
+tags:
+- generated_from_trainer
+metrics:
+- recall
+- accuracy
+model-index:
+- name: multibert_testrun
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# multibert_testrun
+
+This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4300
+- Precisions: 0.8488
+- Recall: 0.7908
+- F-measure: 0.8172
+- Accuracy: 0.9404
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 7.5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 14
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
+| 0.4196        | 1.0   | 269  | 0.3190          | 0.8426     | 0.7090 | 0.7230    | 0.9078   |
+| 0.2111        | 2.0   | 538  | 0.2981          | 0.7730     | 0.7491 | 0.7551    | 0.9190   |
+| 0.1275        | 3.0   | 807  | 0.2666          | 0.8158     | 0.7744 | 0.7915    | 0.9346   |
+| 0.0868        | 4.0   | 1076 | 0.2929          | 0.8276     | 0.7891 | 0.8050    | 0.9349   |
+| 0.0608        | 5.0   | 1345 | 0.3253          | 0.8370     | 0.7803 | 0.8043    | 0.9353   |
+| 0.0353        | 6.0   | 1614 | 0.3723          | 0.8153     | 0.7999 | 0.8051    | 0.9360   |
+| 0.0254        | 7.0   | 1883 | 0.4149          | 0.8266     | 0.7688 | 0.7934    | 0.9339   |
+| 0.0203        | 8.0   | 2152 | 0.4399          | 0.8356     | 0.7755 | 0.8028    | 0.9357   |
+| 0.0146        | 9.0   | 2421 | 0.4413          | 0.8295     | 0.7845 | 0.8045    | 0.9349   |
+| 0.0108        | 10.0  | 2690 | 0.4300          | 0.8488     | 0.7908 | 0.8172    | 0.9404   |
+| 0.0054        | 11.0  | 2959 | 0.4428          | 0.8317     | 0.7858 | 0.8062    | 0.9357   |
+| 0.004         | 12.0  | 3228 | 0.4681          | 0.8403     | 0.7861 | 0.8095    | 0.9375   |
+| 0.0019        | 13.0  | 3497 | 0.4725          | 0.8409     | 0.7901 | 0.8123    | 0.9386   |
+| 0.0013        | 14.0  | 3766 | 0.4839          | 0.8437     | 0.7895 | 0.8137    | 0.9404   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

pytorch_model.bin

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