Woohoo! Drishti :)

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: distilbert-base-multilingual-cased-language-detection-fp16-true-bs-128
+  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-language-detection-fp16-true-bs-128
+
+This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0132
+- Accuracy: 0.9985
+- Weighted f1: 0.9985
+- Micro f1: 0.9985
+- Macro f1: 0.9984
+- Weighted recall: 0.9985
+- Micro recall: 0.9985
+- Macro recall: 0.9984
+- Weighted precision: 0.9985
+- Micro precision: 0.9985
+- Macro precision: 0.9985
+
+## 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: 128
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
+| 0.2777        | 1.0   | 83   | 0.0230          | 0.9947   | 0.9947      | 0.9947   | 0.9946   | 0.9947          | 0.9947       | 0.9946       | 0.9947             | 0.9947          | 0.9946          |
+| 0.0189        | 2.0   | 166  | 0.0132          | 0.9985   | 0.9985      | 0.9985   | 0.9984   | 0.9985          | 0.9985       | 0.9984       | 0.9985             | 0.9985          | 0.9985          |
+| 0.0054        | 3.0   | 249  | 0.0084          | 0.9985   | 0.9985      | 0.9985   | 0.9985   | 0.9985          | 0.9985       | 0.9985       | 0.9985             | 0.9985          | 0.9985          |
+| 0.0027        | 4.0   | 332  | 0.0078          | 0.9985   | 0.9985      | 0.9985   | 0.9985   | 0.9985          | 0.9985       | 0.9985       | 0.9985             | 0.9985          | 0.9985          |
+| 0.0022        | 5.0   | 415  | 0.0084          | 0.9985   | 0.9985      | 0.9985   | 0.9985   | 0.9985          | 0.9985       | 0.9985       | 0.9985             | 0.9985          | 0.9985          |
+
+
+### Framework versions
+
+- Transformers 4.33.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4.dev0
+- Tokenizers 0.13.3

pytorch_model.bin

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