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Woohoo! Drishti :)
Browse files- README.md +73 -0
- pytorch_model.bin +1 -1
README.md
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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-64
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results: []
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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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# distilbert-base-multilingual-cased-language-detection-fp16-false-bs-64
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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: 0.0103
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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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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 64
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- eval_batch_size: 64
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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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### Training results
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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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| 0.1689 | 1.0 | 165 | 0.0103 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
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| 0.0096 | 2.0 | 330 | 0.0115 | 0.9977 | 0.9977 | 0.9977 | 0.9977 | 0.9977 | 0.9977 | 0.9977 | 0.9977 | 0.9977 | 0.9977 |
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| 0.0027 | 3.0 | 495 | 0.0032 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
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| 0.0011 | 4.0 | 660 | 0.0022 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
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| 0.0007 | 5.0 | 825 | 0.0027 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 |
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### Framework versions
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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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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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size 541343405
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