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--- |
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license: apache-2.0 |
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base_model: albert-base-v2 |
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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: ALBERT_trainer_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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config: split |
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split: validation |
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args: split |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.927 |
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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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# ALBERT_trainer_emotion |
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co./albert-base-v2) on the emotion dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3559 |
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- Accuracy: 0.927 |
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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: 20 |
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- eval_batch_size: 16 |
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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: 7 |
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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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| 0.1217 | 1.0 | 800 | 0.1936 | 0.93 | |
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| 0.1054 | 2.0 | 1600 | 0.2105 | 0.9305 | |
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| 0.0893 | 3.0 | 2400 | 0.2199 | 0.933 | |
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| 0.0751 | 4.0 | 3200 | 0.2412 | 0.9375 | |
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| 0.0608 | 5.0 | 4000 | 0.2853 | 0.932 | |
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| 0.0342 | 6.0 | 4800 | 0.3575 | 0.9315 | |
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| 0.025 | 7.0 | 5600 | 0.3698 | 0.931 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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