End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert-base-multilingual-cased-FakeNews-Dravidian-mBert
+  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. -->
+
+# bert-base-multilingual-cased-FakeNews-Dravidian-mBert
+
+This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4452
+- Accuracy: 0.8307
+- Weighted f1 score: 0.8305
+- Macro f1 score: 0.8305
+
+## 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-06
+- 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: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 score | Macro f1 score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------:|
+| 0.7901        | 1.0   | 204  | 0.6155          | 0.7067   | 0.6999            | 0.7000         |
+| 0.5829        | 2.0   | 408  | 0.4932          | 0.8037   | 0.8036            | 0.8036         |
+| 0.4813        | 3.0   | 612  | 0.4437          | 0.8135   | 0.8130            | 0.8129         |
+| 0.4298        | 4.0   | 816  | 0.4182          | 0.8123   | 0.8123            | 0.8123         |
+| 0.3896        | 5.0   | 1020 | 0.4068          | 0.8221   | 0.8219            | 0.8219         |
+| 0.3411        | 6.0   | 1224 | 0.3999          | 0.8209   | 0.8209            | 0.8209         |
+| 0.314         | 7.0   | 1428 | 0.4030          | 0.8307   | 0.8305            | 0.8305         |
+| 0.2982        | 8.0   | 1632 | 0.4084          | 0.8270   | 0.8269            | 0.8269         |
+| 0.279         | 9.0   | 1836 | 0.4129          | 0.8319   | 0.8316            | 0.8315         |
+| 0.2502        | 10.0  | 2040 | 0.4120          | 0.8307   | 0.8306            | 0.8305         |
+| 0.2328        | 11.0  | 2244 | 0.4256          | 0.8368   | 0.8364            | 0.8364         |
+| 0.2168        | 12.0  | 2448 | 0.4480          | 0.8393   | 0.8388            | 0.8388         |
+| 0.2246        | 13.0  | 2652 | 0.4463          | 0.8294   | 0.8292            | 0.8292         |
+| 0.2149        | 14.0  | 2856 | 0.4411          | 0.8307   | 0.8306            | 0.8305         |
+| 0.2077        | 15.0  | 3060 | 0.4452          | 0.8307   | 0.8305            | 0.8305         |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.0.0
+- Datasets 2.11.0
+- Tokenizers 0.14.1

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