End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-multilingual-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: multibertfinetuned2408
+  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. -->
+
+# multibertfinetuned2408
+
+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: 0.4196
+- Precision: 0.7180
+- Recall: 0.7032
+- F1: 0.7105
+- Accuracy: 0.8966
+
+## 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: 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: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 236  | 0.4870          | 0.6425    | 0.5817 | 0.6106 | 0.8591   |
+| No log        | 2.0   | 472  | 0.4357          | 0.6814    | 0.7070 | 0.6939 | 0.8851   |
+| 0.457         | 3.0   | 708  | 0.4196          | 0.7180    | 0.7032 | 0.7105 | 0.8966   |
+| 0.457         | 4.0   | 944  | 0.4559          | 0.7308    | 0.7614 | 0.7458 | 0.9024   |
+| 0.1683        | 5.0   | 1180 | 0.4948          | 0.7497    | 0.7577 | 0.7537 | 0.9043   |
+| 0.1683        | 6.0   | 1416 | 0.5416          | 0.7376    | 0.7426 | 0.7401 | 0.9018   |
+| 0.0715        | 7.0   | 1652 | 0.5537          | 0.7548    | 0.7614 | 0.7581 | 0.9077   |
+| 0.0715        | 8.0   | 1888 | 0.5792          | 0.7580    | 0.7608 | 0.7594 | 0.9079   |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

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