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MiniLM_classification_tools_fr

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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  1. README.md +97 -0
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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: microsoft/Multilingual-MiniLM-L12-H384
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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: MiniLM_classification_tools_fr
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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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+ # MiniLM_classification_tools_fr
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+
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+ This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7694
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+ - Accuracy: 0.75
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+ - Learning Rate: 0.0000
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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: 0.0001
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+ - train_batch_size: 24
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+ - eval_batch_size: 192
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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: 60
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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 | Rate |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 7 | 2.0620 | 0.35 | 0.0001 |
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+ | No log | 2.0 | 14 | 1.9515 | 0.425 | 0.0001 |
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+ | No log | 3.0 | 21 | 1.7736 | 0.45 | 0.0001 |
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+ | No log | 4.0 | 28 | 1.6055 | 0.475 | 0.0001 |
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+ | No log | 5.0 | 35 | 1.5108 | 0.5 | 0.0001 |
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+ | No log | 6.0 | 42 | 1.4074 | 0.45 | 9e-05 |
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+ | No log | 7.0 | 49 | 1.3848 | 0.475 | 0.0001 |
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+ | No log | 8.0 | 56 | 1.2533 | 0.625 | 0.0001 |
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+ | No log | 9.0 | 63 | 1.2463 | 0.525 | 0.0001 |
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+ | No log | 10.0 | 70 | 1.1593 | 0.6 | 0.0001 |
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+ | No log | 11.0 | 77 | 1.1637 | 0.6 | 0.0001 |
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+ | No log | 12.0 | 84 | 1.0900 | 0.625 | 8e-05 |
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+ | No log | 13.0 | 91 | 0.9577 | 0.7 | 0.0001 |
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+ | No log | 14.0 | 98 | 0.9465 | 0.675 | 0.0001 |
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+ | No log | 15.0 | 105 | 0.9255 | 0.675 | 0.0001 |
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+ | No log | 16.0 | 112 | 0.8836 | 0.675 | 0.0001 |
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+ | No log | 17.0 | 119 | 0.8307 | 0.675 | 0.0001 |
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+ | No log | 18.0 | 126 | 0.8335 | 0.725 | 7e-05 |
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+ | No log | 19.0 | 133 | 0.8469 | 0.625 | 0.0001 |
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+ | No log | 20.0 | 140 | 0.7384 | 0.75 | 0.0001 |
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+ | No log | 21.0 | 147 | 0.7330 | 0.775 | 0.0001 |
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+ | No log | 22.0 | 154 | 0.7811 | 0.775 | 0.0001 |
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+ | No log | 23.0 | 161 | 0.6857 | 0.8 | 0.0001 |
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+ | No log | 24.0 | 168 | 0.6733 | 0.825 | 6e-05 |
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+ | No log | 25.0 | 175 | 0.6510 | 0.85 | 0.0001 |
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+ | No log | 26.0 | 182 | 0.6363 | 0.85 | 0.0001 |
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+ | No log | 27.0 | 189 | 0.6101 | 0.875 | 0.0001 |
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+ | No log | 28.0 | 196 | 0.6434 | 0.8 | 0.0001 |
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+ | No log | 29.0 | 203 | 0.6644 | 0.775 | 0.0001 |
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+ | No log | 30.0 | 210 | 0.7162 | 0.75 | 5e-05 |
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+ | No log | 31.0 | 217 | 0.7422 | 0.775 | 0.0000 |
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+ | No log | 32.0 | 224 | 0.7120 | 0.775 | 0.0000 |
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+ | No log | 33.0 | 231 | 0.6296 | 0.8 | 0.0000 |
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+ | No log | 34.0 | 238 | 0.6522 | 0.775 | 0.0000 |
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+ | No log | 35.0 | 245 | 0.7636 | 0.75 | 0.0000 |
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+ | No log | 36.0 | 252 | 0.7703 | 0.75 | 4e-05 |
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+ | No log | 37.0 | 259 | 0.7694 | 0.75 | 0.0000 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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