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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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- emotion
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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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- 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: emotion
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type: emotion
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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: 0.934
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- name: F1
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type: f1
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value: 0.9337817808480242
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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 the emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2155
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- Accuracy: 0.934
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- F1: 0.9338
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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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| 0.1768 | 1.0 | 250 | 0.1867 | 0.924 | 0.9235 |
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| 0.1227 | 2.0 | 500 | 0.1588 | 0.934 | 0.9346 |
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| 0.1031 | 3.0 | 750 | 0.1656 | 0.931 | 0.9306 |
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| 0.0843 | 4.0 | 1000 | 0.1662 | 0.9395 | 0.9392 |
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| 0.0662 | 5.0 | 1250 | 0.1714 | 0.9325 | 0.9326 |
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| 0.0504 | 6.0 | 1500 | 0.1821 | 0.934 | 0.9338 |
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| 0.0429 | 7.0 | 1750 | 0.2038 | 0.933 | 0.9324 |
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| 0.0342 | 8.0 | 2000 | 0.2054 | 0.938 | 0.9379 |
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| 0.0296 | 9.0 | 2250 | 0.2128 | 0.9345 | 0.9345 |
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| 0.0211 | 10.0 | 2500 | 0.2155 | 0.934 | 0.9338 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.10.0+cu113
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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