distilBERT_token_itr0_1e-05_editorials_01_03_2022-15_12_47
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: 0.1194
- Precision: 0.0637
- Recall: 0.0080
- F1: 0.0141
- Accuracy: 0.9707
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: 1e-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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 15 | 0.0877 | 0.12 | 0.0194 | 0.0333 | 0.9830 |
No log | 2.0 | 30 | 0.0806 | 0.12 | 0.0194 | 0.0333 | 0.9830 |
No log | 3.0 | 45 | 0.0758 | 0.12 | 0.0194 | 0.0333 | 0.9830 |
No log | 4.0 | 60 | 0.0741 | 0.12 | 0.0194 | 0.0333 | 0.9830 |
No log | 5.0 | 75 | 0.0741 | 0.12 | 0.0194 | 0.0333 | 0.9830 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3
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