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-false-bs-4
+  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-false-bs-4
+
+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: 0.0000
+- Accuracy: 1.0
+- Weighted f1: 1.0
+- Micro f1: 1.0
+- Macro f1: 1.0
+- Weighted recall: 1.0
+- Micro recall: 1.0
+- Macro recall: 1.0
+- Weighted precision: 1.0
+- Micro precision: 1.0
+- Macro precision: 1.0
+
+## 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: 4
+- eval_batch_size: 4
+- 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
+| 0.0634        | 1.0   | 2630  | 0.0038          | 0.9985   | 0.9985      | 0.9985   | 0.9985   | 0.9985          | 0.9985       | 0.9985       | 0.9985             | 0.9985          | 0.9984          |
+| 0.0094        | 2.0   | 5260  | 0.0040          | 0.9992   | 0.9992      | 0.9992   | 0.9992   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9992          |
+| 0.001         | 3.0   | 7890  | 0.0069          | 0.9992   | 0.9992      | 0.9992   | 0.9992   | 0.9992          | 0.9992       | 0.9993       | 0.9992             | 0.9992          | 0.9992          |
+| 0.0009        | 4.0   | 10520 | 0.0000          | 1.0      | 1.0         | 1.0      | 1.0      | 1.0             | 1.0          | 1.0          | 1.0                | 1.0             | 1.0             |
+| 0.0           | 5.0   | 13150 | 0.0000          | 1.0      | 1.0         | 1.0      | 1.0      | 1.0             | 1.0          | 1.0          | 1.0                | 1.0             | 1.0             |
+
+
+### 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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