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README.md
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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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metrics:
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- accuracy
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- f1
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- precision
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model-index:
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- name: distilbert-base-uncased_emotion_ft_0719
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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_emotion_ft_0719
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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: 0.1561
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- Accuracy: 0.9355
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- F1: 0.9356
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- Precision: 0.9158
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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: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
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| 0.7862 | 1.0 | 250 | 0.2734 | 0.9105 | 0.9104 | 0.9016 |
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| 0.2059 | 2.0 | 500 | 0.1821 | 0.9365 | 0.9372 | 0.9058 |
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| 0.1394 | 3.0 | 750 | 0.1708 | 0.9335 | 0.9340 | 0.9110 |
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| 0.1098 | 4.0 | 1000 | 0.1561 | 0.9355 | 0.9356 | 0.9158 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Tokenizers 0.13.3
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