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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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datasets: |
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- twitter-sentiment-analysis |
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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: twitter-sentiment-analysis-v2 |
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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: twitter-sentiment-analysis |
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type: twitter-sentiment-analysis |
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config: default |
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split: test |
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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: 0.8366721507145392 |
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- name: F1 |
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type: f1 |
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value: 0.8366721507145392 |
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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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# twitter-sentiment-analysis-v2 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the twitter-sentiment-analysis dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3771 |
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- Accuracy: 0.8367 |
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- F1: 0.8367 |
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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: reduce_lr_on_plateau |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 3 |
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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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| 0.3957 | 0.13 | 1000 | 0.4273 | 0.8075 | 0.8005 | |
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| 0.4086 | 0.27 | 2000 | 0.4081 | 0.8211 | 0.8139 | |
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| 0.4085 | 0.4 | 3000 | 0.3971 | 0.8274 | 0.8237 | |
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| 0.3936 | 0.53 | 4000 | 0.3857 | 0.8304 | 0.8307 | |
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| 0.3783 | 0.67 | 5000 | 0.3978 | 0.8317 | 0.8300 | |
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| 0.3858 | 0.8 | 6000 | 0.3887 | 0.8281 | 0.8182 | |
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| 0.3779 | 0.93 | 7000 | 0.3771 | 0.8367 | 0.8367 | |
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| 0.2971 | 1.07 | 8000 | 0.4023 | 0.8352 | 0.8310 | |
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| 0.2994 | 1.2 | 9000 | 0.3865 | 0.8326 | 0.8342 | |
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| 0.293 | 1.33 | 10000 | 0.4454 | 0.8299 | 0.8197 | |
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| 0.3053 | 1.47 | 11000 | 0.3929 | 0.8364 | 0.8349 | |
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| 0.3125 | 1.6 | 12000 | 0.4141 | 0.8366 | 0.8314 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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