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README.md
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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: tiny-mlm-tweet-target-tweet
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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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config: emotion
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split: train
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args: emotion
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7165775401069518
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- name: F1
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type: f1
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value: 0.7162540037184906
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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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# tiny-mlm-tweet-target-tweet
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This model is a fine-tuned version of [muhtasham/tiny-mlm-tweet](https://huggingface.co/muhtasham/tiny-mlm-tweet) on the tweet_eval dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2643
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- Accuracy: 0.7166
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- F1: 0.7163
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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: constant
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- num_epochs: 200
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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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| 1.1435 | 4.9 | 500 | 0.9732 | 0.6604 | 0.6283 |
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| 0.7389 | 9.8 | 1000 | 0.8571 | 0.6898 | 0.6780 |
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| 0.5057 | 14.71 | 1500 | 0.8324 | 0.6979 | 0.6929 |
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| 0.3466 | 19.61 | 2000 | 0.9128 | 0.6925 | 0.6945 |
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| 0.2395 | 24.51 | 2500 | 0.9487 | 0.7166 | 0.7192 |
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| 0.1649 | 29.41 | 3000 | 1.0338 | 0.7166 | 0.7172 |
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| 0.119 | 34.31 | 3500 | 1.1793 | 0.7112 | 0.7144 |
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| 0.0882 | 39.22 | 4000 | 1.2643 | 0.7166 | 0.7163 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.12.1
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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