finetuned_token_itr0_0.0002_all_16_02_2022-20_14_27
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: 0.1588
- Precision: 0.4510
- Recall: 0.5622
- F1: 0.5005
- Accuracy: 0.9477
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: 0.0002
- 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 | 0.2896 | 0.1483 | 0.1981 | 0.1696 | 0.8745 |
| No log | 2.0 | 76 | 0.2553 | 0.2890 | 0.3604 | 0.3207 | 0.8918 |
| No log | 3.0 | 114 | 0.2507 | 0.246 | 0.4642 | 0.3216 | 0.8925 |
| No log | 4.0 | 152 | 0.2540 | 0.2428 | 0.4792 | 0.3223 | 0.8922 |
| No log | 5.0 | 190 | 0.2601 | 0.2747 | 0.4717 | 0.3472 | 0.8965 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3