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: multibertfinetuned2209
+  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. -->
+
+# multibertfinetuned2209
+
+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: 0.3973
+- Precision: 0.7567
+- Recall: 0.7607
+- F1: 0.7587
+- Accuracy: 0.9064
+
+## 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: 32
+- eval_batch_size: 32
+- 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   | 118  | 0.4058          | 0.7597    | 0.7343 | 0.7468 | 0.9032   |
+| No log        | 2.0   | 236  | 0.3973          | 0.7567    | 0.7607 | 0.7587 | 0.9064   |
+| No log        | 3.0   | 354  | 0.4153          | 0.7540    | 0.7677 | 0.7608 | 0.9062   |
+| No log        | 4.0   | 472  | 0.4656          | 0.7645    | 0.7466 | 0.7555 | 0.9082   |
+| 0.0692        | 5.0   | 590  | 0.4940          | 0.7594    | 0.7554 | 0.7574 | 0.9043   |
+| 0.0692        | 6.0   | 708  | 0.5446          | 0.7668    | 0.7484 | 0.7575 | 0.9059   |
+| 0.0692        | 7.0   | 826  | 0.5732          | 0.7818    | 0.7420 | 0.7613 | 0.9069   |
+| 0.0692        | 8.0   | 944  | 0.5668          | 0.7844    | 0.7431 | 0.7632 | 0.9082   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

pytorch_model.bin

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