End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- recall
+model-index:
+- name: temp_model
+  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. -->
+
+# temp_model
+
+This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1977
+- Accuracy: 0.9383
+- F1: 0.2445
+- Recall: 0.1628
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
+| 0.2118        | 1.0   | 701  | 0.2022          | 0.9340   | 0.1148 | 0.0698 |
+| 0.1864        | 2.0   | 1402 | 0.2178          | 0.9397   | 0.0452 | 0.0233 |
+| 0.1275        | 3.0   | 2103 | 0.1977          | 0.9383   | 0.2445 | 0.1628 |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

runs/Jan05_01-33-15_be6bed7a2f79/events.out.tfevents.1736040801.be6bed7a2f79.20456.1

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