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distilbert-base-uncased-english-sentweet-profane
This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0661
- Accuracy: 0.7917
- Precision: 0.7961
- Recall: 0.7982
- F1: 0.7916
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: 5e-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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 81 | 0.4663 | 0.8090 | 0.8246 | 0.8205 | 0.8089 |
| No log | 2.0 | 162 | 0.5420 | 0.8160 | 0.8339 | 0.8282 | 0.8158 |
| No log | 3.0 | 243 | 0.6331 | 0.7917 | 0.7907 | 0.7938 | 0.7908 |
| No log | 4.0 | 324 | 0.9114 | 0.7986 | 0.8019 | 0.8044 | 0.7985 |
| No log | 5.0 | 405 | 0.9580 | 0.8021 | 0.8029 | 0.8061 | 0.8017 |
| No log | 6.0 | 486 | 1.0661 | 0.7917 | 0.7961 | 0.7982 | 0.7916 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.1+cu117
- Datasets 2.6.1
- Tokenizers 0.11.0
