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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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- go_emotions
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metrics:
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- f1
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- accuracy
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model-index:
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- name: bert-base-goemotions
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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: go_emotions
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type: go_emotions
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config: simplified
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split: validation
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args: simplified
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metrics:
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- name: F1
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type: f1
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value: 0.5726694586629439
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- name: Accuracy
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type: accuracy
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value: 0.4375230372281607
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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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# bert-base-goemotions
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the go_emotions dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1539
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- F1: 0.5727
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- Roc Auc: 0.7796
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- Accuracy: 0.4375
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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: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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 | F1 | Roc Auc | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
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| 0.0833 | 1.0 | 2714 | 0.0876 | 0.5453 | 0.7189 | 0.4243 |
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| 0.0719 | 2.0 | 5428 | 0.0867 | 0.5586 | 0.7322 | 0.4399 |
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| 0.0575 | 3.0 | 8142 | 0.0943 | 0.5736 | 0.7523 | 0.4665 |
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| 0.0411 | 4.0 | 10856 | 0.1064 | 0.5655 | 0.7580 | 0.4574 |
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| 0.0301 | 5.0 | 13570 | 0.1167 | 0.5622 | 0.7591 | 0.4517 |
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| 0.0217 | 6.0 | 16284 | 0.1279 | 0.5579 | 0.7648 | 0.4375 |
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| 0.015 | 7.0 | 18998 | 0.1367 | 0.5663 | 0.7759 | 0.4333 |
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| 0.0102 | 8.0 | 21712 | 0.1445 | 0.5695 | 0.7793 | 0.4322 |
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| 0.0077 | 9.0 | 24426 | 0.1491 | 0.5725 | 0.7795 | 0.4366 |
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| 0.0057 | 10.0 | 27140 | 0.1539 | 0.5727 | 0.7796 | 0.4375 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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