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update model card README.md
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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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- precision
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model-index:
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- name: distilbert-base-uncased_emotion_ft_0416
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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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config: split
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split: validation
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args: split
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9325
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- name: F1
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type: f1
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value: 0.9327439172316551
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- name: Precision
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type: precision
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value: 0.9027697506235867
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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_0416
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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: 0.1714
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- Accuracy: 0.9325
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- F1: 0.9327
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- Precision: 0.9028
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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: 128
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- eval_batch_size: 128
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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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| No log | 1.0 | 125 | 0.4267 | 0.877 | 0.8677 | 0.8778 |
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| 0.6498 | 2.0 | 250 | 0.2128 | 0.922 | 0.9219 | 0.8975 |
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| 0.6498 | 3.0 | 375 | 0.1880 | 0.925 | 0.9258 | 0.8877 |
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| 0.1653 | 4.0 | 500 | 0.1714 | 0.9325 | 0.9327 | 0.9028 |
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.11.0
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