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distilbert-base-uncased-emotions-augmented
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6063
- Accuracy: 0.7789
- F1: 0.7770
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.855 | 1.0 | 819 | 0.6448 | 0.7646 | 0.7606 |
0.5919 | 2.0 | 1638 | 0.6067 | 0.7745 | 0.7730 |
0.5077 | 3.0 | 2457 | 0.6063 | 0.7789 | 0.7770 |
0.4364 | 4.0 | 3276 | 0.6342 | 0.7725 | 0.7687 |
0.3698 | 5.0 | 4095 | 0.6832 | 0.7693 | 0.7686 |
0.3153 | 6.0 | 4914 | 0.7364 | 0.7636 | 0.7596 |
0.2723 | 7.0 | 5733 | 0.7578 | 0.7661 | 0.7648 |
0.2429 | 8.0 | 6552 | 0.7816 | 0.7623 | 0.7599 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1