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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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