End of training

README.md

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+---
+license: mit
+base_model: ai4bharat/indic-bert
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: indic-bert-FakeNews-Dravidiant
+  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. -->
+
+# indic-bert-FakeNews-Dravidiant
+
+This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6230
+- Accuracy: 0.6822
+- Weighted f1 score: 0.6816
+- Macro f1 score: 0.6816
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 score | Macro f1 score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------:|
+| 1.0142        | 1.0   | 204  | 0.7823          | 0.5509   | 0.5402            | 0.5405         |
+| 0.7202        | 2.0   | 408  | 0.6967          | 0.5902   | 0.5747            | 0.5744         |
+| 0.6758        | 3.0   | 612  | 0.6730          | 0.6319   | 0.6224            | 0.6221         |
+| 0.6471        | 4.0   | 816  | 0.6547          | 0.6417   | 0.6336            | 0.6334         |
+| 0.6221        | 5.0   | 1020 | 0.6396          | 0.6663   | 0.6646            | 0.6645         |
+| 0.6005        | 6.0   | 1224 | 0.6322          | 0.6724   | 0.6723            | 0.6723         |
+| 0.5801        | 7.0   | 1428 | 0.6385          | 0.6601   | 0.6530            | 0.6528         |
+| 0.5613        | 8.0   | 1632 | 0.6249          | 0.6810   | 0.6797            | 0.6796         |
+| 0.5534        | 9.0   | 1836 | 0.6231          | 0.6834   | 0.6831            | 0.6831         |
+| 0.5428        | 10.0  | 2040 | 0.6230          | 0.6822   | 0.6816            | 0.6816         |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.0.0
+- Datasets 2.11.0
+- Tokenizers 0.14.1

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