Training Complete

README.md

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+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert-base-multilingual-cased-finetuned
+  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. -->
+
+# distilbert-base-multilingual-cased-finetuned
+
+This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6740
+- Accuracy: 0.6643
+- F1: 0.6611
+
+## 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: 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.4725        | 1.0   | 252  | 1.0892          | 0.6604   | 0.6625 |
+| 0.3392        | 2.0   | 504  | 1.2096          | 0.6594   | 0.6649 |
+| 0.2575        | 3.0   | 756  | 1.2745          | 0.6723   | 0.6706 |
+| 0.1979        | 4.0   | 1008 | 1.3719          | 0.6713   | 0.6666 |
+| 0.1757        | 5.0   | 1260 | 1.4239          | 0.6723   | 0.6652 |
+| 0.1414        | 6.0   | 1512 | 1.5074          | 0.6663   | 0.6666 |
+| 0.1073        | 7.0   | 1764 | 1.5703          | 0.6783   | 0.6722 |
+| 0.0812        | 8.0   | 2016 | 1.6218          | 0.6673   | 0.6638 |
+| 0.0615        | 9.0   | 2268 | 1.6676          | 0.6693   | 0.6642 |
+| 0.0531        | 10.0  | 2520 | 1.6740          | 0.6643   | 0.6611 |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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