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README.md
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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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<!-- 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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# minilm-fintuned-emotion
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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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## 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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- mixed_precision_training: Native AMP
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### Training results
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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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### Framework versions
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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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