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Woohoo! Drishti :)

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  1. README.md +73 -0
  2. pytorch_model.bin +1 -1
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: distilbert-base-multilingual-cased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: distilbert-base-multilingual-cased-language-detection-fp16-false-bs-32
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # distilbert-base-multilingual-cased-language-detection-fp16-false-bs-32
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+
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+ This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0040
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+ - Accuracy: 0.9992
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+ - Weighted f1: 0.9992
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+ - Micro f1: 0.9992
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+ - Macro f1: 0.9992
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+ - Weighted recall: 0.9992
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+ - Micro recall: 0.9992
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+ - Macro recall: 0.9992
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+ - Weighted precision: 0.9992
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+ - Micro precision: 0.9992
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+ - Macro precision: 0.9992
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | 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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
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+ | 0.1131 | 1.0 | 329 | 0.0040 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
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+ | 0.0058 | 2.0 | 658 | 0.0063 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 |
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+ | 0.0013 | 3.0 | 987 | 0.0061 | 0.9985 | 0.9985 | 0.9985 | 0.9984 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | 0.9984 |
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+ | 0.0003 | 4.0 | 1316 | 0.0036 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
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+ | 0.0002 | 5.0 | 1645 | 0.0037 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0.dev0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.4.dev0
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+ - Tokenizers 0.13.3
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