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: multibert0510_lrate7.5b16
+  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. -->
+
+# multibert0510_lrate7.5b16
+
+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: 0.5930
+- Precisions: 0.8750
+- Recall: 0.8217
+- F-measure: 0.8450
+- Accuracy: 0.9133
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
+| 0.6022        | 1.0   | 236  | 0.4256          | 0.8484     | 0.6548 | 0.6844    | 0.8642   |
+| 0.3396        | 2.0   | 472  | 0.3851          | 0.8046     | 0.7225 | 0.7312    | 0.8773   |
+| 0.2116        | 3.0   | 708  | 0.3670          | 0.8311     | 0.7347 | 0.7560    | 0.8947   |
+| 0.148         | 4.0   | 944  | 0.4016          | 0.8827     | 0.7716 | 0.8081    | 0.9021   |
+| 0.0959        | 5.0   | 1180 | 0.4409          | 0.8338     | 0.8054 | 0.8166    | 0.8998   |
+| 0.0809        | 6.0   | 1416 | 0.4964          | 0.8678     | 0.7356 | 0.7799    | 0.8980   |
+| 0.056         | 7.0   | 1652 | 0.4894          | 0.8451     | 0.7520 | 0.7855    | 0.8931   |
+| 0.038         | 8.0   | 1888 | 0.5008          | 0.8697     | 0.8024 | 0.8301    | 0.9104   |
+| 0.031         | 9.0   | 2124 | 0.4813          | 0.8561     | 0.8172 | 0.8335    | 0.9122   |
+| 0.02          | 10.0  | 2360 | 0.5857          | 0.8831     | 0.7946 | 0.8305    | 0.9115   |
+| 0.0129        | 11.0  | 2596 | 0.5622          | 0.8667     | 0.8039 | 0.8308    | 0.9098   |
+| 0.0113        | 12.0  | 2832 | 0.5861          | 0.8746     | 0.8015 | 0.8324    | 0.9104   |
+| 0.0065        | 13.0  | 3068 | 0.5964          | 0.8752     | 0.8204 | 0.8443    | 0.9128   |
+| 0.004         | 14.0  | 3304 | 0.5930          | 0.8750     | 0.8217 | 0.8450    | 0.9133   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.0

pytorch_model.bin

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