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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tweet_eval |
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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-tweets-sentiment |
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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: tweet_eval |
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type: tweet_eval |
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args: sentiment |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7295 |
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- name: F1 |
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type: f1 |
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value: 0.7303196028048928 |
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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-tweets-sentiment |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8192 |
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- Accuracy: 0.7295 |
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- F1: 0.7303 |
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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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| 0.7126 | 1.0 | 713 | 0.6578 | 0.7185 | 0.7181 | |
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| 0.5514 | 2.0 | 1426 | 0.6249 | 0.7005 | 0.7046 | |
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| 0.4406 | 3.0 | 2139 | 0.7053 | 0.731 | 0.7296 | |
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| 0.3511 | 4.0 | 2852 | 0.7580 | 0.718 | 0.7180 | |
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| 0.2809 | 5.0 | 3565 | 0.8192 | 0.7295 | 0.7303 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0 |
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- Datasets 1.16.1 |
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- Tokenizers 0.10.3 |
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