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_1210seed25
+  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_1210seed25
+
+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: 0.4453
+- Precisions: 0.8647
+- Recall: 0.8314
+- F-measure: 0.8459
+- Accuracy: 0.9141
+
+## 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: 25
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
+| 0.6013        | 1.0   | 236  | 0.4080          | 0.8974     | 0.6857 | 0.7273    | 0.8736   |
+| 0.319         | 2.0   | 472  | 0.3621          | 0.8338     | 0.7306 | 0.7317    | 0.8875   |
+| 0.1929        | 3.0   | 708  | 0.3823          | 0.8020     | 0.7680 | 0.7761    | 0.9022   |
+| 0.1389        | 4.0   | 944  | 0.4353          | 0.8400     | 0.7742 | 0.7990    | 0.9003   |
+| 0.0958        | 5.0   | 1180 | 0.4348          | 0.8726     | 0.7547 | 0.7971    | 0.9011   |
+| 0.0676        | 6.0   | 1416 | 0.4453          | 0.8647     | 0.8314 | 0.8459    | 0.9141   |
+| 0.0506        | 7.0   | 1652 | 0.5222          | 0.8555     | 0.8013 | 0.8253    | 0.9100   |
+| 0.0315        | 8.0   | 1888 | 0.5192          | 0.8700     | 0.7873 | 0.8187    | 0.9108   |
+| 0.0229        | 9.0   | 2124 | 0.5977          | 0.8402     | 0.7839 | 0.8079    | 0.9062   |
+| 0.0149        | 10.0  | 2360 | 0.6061          | 0.8622     | 0.8069 | 0.8305    | 0.9131   |
+| 0.0122        | 11.0  | 2596 | 0.5894          | 0.8419     | 0.7702 | 0.7983    | 0.9085   |
+| 0.0065        | 12.0  | 2832 | 0.6120          | 0.8514     | 0.7700 | 0.8021    | 0.9089   |
+| 0.0039        | 13.0  | 3068 | 0.6434          | 0.8437     | 0.7646 | 0.7965    | 0.9055   |
+| 0.003         | 14.0  | 3304 | 0.6391          | 0.8403     | 0.7670 | 0.7973    | 0.9062   |
+
+
+### 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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