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finetuned_token_2e-05_all_16_02_2022-15_41_15
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: 0.1742
- Precision: 0.3447
- Recall: 0.3410
- F1: 0.3428
- Accuracy: 0.9455
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 38 | 0.3692 | 0.0868 | 0.2030 | 0.1216 | 0.8238 |
| No log | 2.0 | 76 | 0.3198 | 0.1674 | 0.3029 | 0.2157 | 0.8567 |
| No log | 3.0 | 114 | 0.3156 | 0.1520 | 0.3096 | 0.2039 | 0.8510 |
| No log | 4.0 | 152 | 0.3129 | 0.1753 | 0.3266 | 0.2281 | 0.8500 |
| No log | 5.0 | 190 | 0.3038 | 0.1716 | 0.3401 | 0.2281 | 0.8595 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3
