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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: microsoft/MiniLM-L12-H384-uncased
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - emotion
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+ model-index:
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+ - name: minilm-fintuned-emotion
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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-fintuned-emotion
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+
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+ This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the emotion dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3605
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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: 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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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 250 | 1.0591 |
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+ | No log | 2.0 | 500 | 0.7041 |
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+ | No log | 3.0 | 750 | 0.4961 |
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+ | No log | 4.0 | 1000 | 0.3879 |
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+ | No log | 5.0 | 1250 | 0.3605 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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