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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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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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- f1 |
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model-index: |
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- name: emotion-analysis-3000 |
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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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# emotion-analysis-3000 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0894 |
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- Accuracy: 0.9417 |
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- F1: 0.9392 |
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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: 16 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
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| 0.0912 | 1.0 | 20841 | 0.0922 | 0.9423 | 0.9436 | |
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| 0.097 | 2.0 | 41682 | 0.0894 | 0.9417 | 0.9392 | |
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| 0.0808 | 3.0 | 62523 | 0.0937 | 0.9419 | 0.9393 | |
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| 0.0852 | 4.0 | 83364 | 0.0989 | 0.9424 | 0.9397 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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