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--- |
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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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metrics: |
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- accuracy |
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model-index: |
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- name: MiniLMv2-L12-H384-emotion |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: emotion |
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type: emotion |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.925 |
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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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# MiniLMv2-L12-H384-emotion |
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This model is a fine-tuned version of [nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large](https://huggingface.co/nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large) on the emotion dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2069 |
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- Accuracy: 0.925 |
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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: 3e-05 |
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- train_batch_size: 16 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 8 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.8745 | 1.0 | 1000 | 0.6673 | 0.81 | |
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| 0.3466 | 2.0 | 2000 | 0.2816 | 0.918 | |
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| 0.2201 | 3.0 | 3000 | 0.2367 | 0.9215 | |
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| 0.1761 | 4.0 | 4000 | 0.2069 | 0.925 | |
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| 0.1435 | 5.0 | 5000 | 0.2089 | 0.922 | |
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| 0.1454 | 6.0 | 6000 | 0.2168 | 0.923 | |
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| 0.1041 | 7.0 | 7000 | 0.2081 | 0.924 | |
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| 0.0953 | 8.0 | 8000 | 0.2133 | 0.9245 | |
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### Framework versions |
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- Transformers 4.12.3 |
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- Pytorch 1.9.1 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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