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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: 0.9275 |
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- name: F1 |
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type: f1 |
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value: 0.9273822408882375 |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: emotion |
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type: emotion |
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config: default |
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split: test |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.919 |
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verified: true |
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- name: Precision Macro |
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type: precision |
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value: 0.8882001804445858 |
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verified: true |
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- name: Precision Micro |
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type: precision |
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value: 0.919 |
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verified: true |
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- name: Precision Weighted |
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type: precision |
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value: 0.9194695149914663 |
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verified: true |
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- name: Recall Macro |
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type: recall |
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value: 0.857858142469294 |
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verified: true |
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- name: Recall Micro |
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type: recall |
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value: 0.919 |
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verified: true |
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- name: Recall Weighted |
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type: recall |
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value: 0.919 |
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verified: true |
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- name: F1 Macro |
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type: f1 |
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value: 0.8684381937860847 |
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verified: true |
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- name: F1 Micro |
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type: f1 |
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value: 0.919 |
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verified: true |
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- name: F1 Weighted |
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type: f1 |
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value: 0.9182406234430719 |
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verified: true |
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- name: loss |
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type: loss |
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value: 0.21632428467273712 |
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verified: true |
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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: 0.2237 |
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- Accuracy: 0.9275 |
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- F1: 0.9274 |
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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: 2 |
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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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| 0.8643 | 1.0 | 250 | 0.3324 | 0.9065 | 0.9025 | |
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| 0.2589 | 2.0 | 500 | 0.2237 | 0.9275 | 0.9274 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 1.16.1 |
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- Tokenizers 0.10.3 |
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