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bert-goemotions-15epochs-run2
mpalaval/bert-goemotions-15epochs-run2
bert-goemotions-15epochs-run2 is a machine learning model from mpalaval. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Nov 15, 2023
- Updated
- Nov 15, 2023
- SHA
- 8d1c069d
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
bert-goemotions-15epochs-run2
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1154
- Accuracy Thresh: 0.9616
- F1 weighted: 0.3672
- F1 macro: 0.2835
- Accuracy: 0.4083
- Recall weighted: 0.4083
- Recall macro: 0.2851
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Thresh | F1 weighted | F1 macro | Accuracy | Recall weighted | Recall macro |
|---|---|---|---|---|---|---|---|---|---|
| 0.1322 | 1.0 | 5283 | 0.1205 | 0.9609 | 0.3371 | 0.2432 | 0.3944 | 0.3944 | 0.2539 |
| 0.1189 | 2.0 | 10566 | 0.1165 | 0.9614 | 0.3573 | 0.2726 | 0.4062 | 0.4062 | 0.2835 |
| 0.114 | 3.0 | 15849 | 0.1154 | 0.9616 | 0.3672 | 0.2835 | 0.4083 | 0.4083 | 0.2851 |
| 0.1098 | 4.0 | 21132 | 0.1157 | 0.9613 | 0.3743 | 0.2929 | 0.4019 | 0.4019 | 0.2996 |
| 0.1059 | 5.0 | 26415 | 0.1172 | 0.9609 | 0.3751 | 0.2959 | 0.4002 | 0.4002 | 0.3049 |
| 0.1023 | 6.0 | 31698 | 0.1173 | 0.9610 | 0.3779 | 0.3012 | 0.3986 | 0.3986 | 0.3135 |
| 0.0988 | 7.0 | 36981 | 0.1188 | 0.9603 | 0.3805 | 0.3082 | 0.3925 | 0.3925 | 0.3175 |
| 0.0956 | 8.0 | 42264 | 0.1199 | 0.9601 | 0.3803 | 0.3044 | 0.3973 | 0.3973 | 0.3129 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 15, 2023
- Updated
- Nov 15, 2023