End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: ai4bharat/indic-bert
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: indic-bert-hinglish-binary
+  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-hinglish-binary
+
+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: 0.7521
+- Accuracy: 0.6681
+- Precision: 0.6338
+- Recall: 0.6182
+- F1: 0.6213
+
+## 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: 128
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- 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 | Precision | Recall | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.6539        | 0.9709 | 25   | 0.6510          | 0.6376   | 0.3188    | 0.5    | 0.3894 |
+| 0.6235        | 1.9806 | 51   | 0.6296          | 0.6376   | 0.3188    | 0.5    | 0.3894 |
+| 0.63          | 2.9903 | 77   | 0.6362          | 0.6376   | 0.3188    | 0.5    | 0.3894 |
+| 0.6149        | 4.0    | 103  | 0.6486          | 0.6376   | 0.3188    | 0.5    | 0.3894 |
+| 0.6088        | 4.9709 | 128  | 0.6229          | 0.6376   | 0.3188    | 0.5    | 0.3894 |
+| 0.5572        | 5.9806 | 154  | 0.6243          | 0.6376   | 0.3188    | 0.5    | 0.3894 |
+| 0.4985        | 6.9903 | 180  | 0.6328          | 0.6322   | 0.3178    | 0.4957 | 0.3873 |
+| 0.4697        | 8.0    | 206  | 0.6893          | 0.6730   | 0.6504    | 0.5829 | 0.5710 |
+| 0.4114        | 8.9709 | 231  | 0.6825          | 0.6839   | 0.6531    | 0.6288 | 0.6327 |
+| 0.3981        | 9.7087 | 250  | 0.6905          | 0.6866   | 0.6582    | 0.6228 | 0.6258 |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0