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--- |
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library_name: transformers |
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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: distilbert-base-uncased-finetuned-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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# distilbert-base-uncased-finetuned-emotion |
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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: 0.2291 |
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- Accuracy: 0.9395 |
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- F1: 0.9395 |
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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: 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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| 0.1313 | 1.0 | 250 | 0.1574 | 0.9355 | 0.9359 | |
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| 0.0897 | 2.0 | 500 | 0.1597 | 0.9375 | 0.9368 | |
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| 0.0818 | 3.0 | 750 | 0.1496 | 0.9395 | 0.9401 | |
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| 0.068 | 4.0 | 1000 | 0.1707 | 0.9365 | 0.9366 | |
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| 0.0533 | 5.0 | 1250 | 0.1842 | 0.9365 | 0.9363 | |
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| 0.043 | 6.0 | 1500 | 0.2020 | 0.9365 | 0.9363 | |
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| 0.0325 | 7.0 | 1750 | 0.2172 | 0.936 | 0.9359 | |
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| 0.0279 | 8.0 | 2000 | 0.2262 | 0.9355 | 0.9353 | |
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| 0.0207 | 9.0 | 2250 | 0.2238 | 0.939 | 0.9392 | |
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| 0.0188 | 10.0 | 2500 | 0.2291 | 0.9395 | 0.9395 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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