finetuned_token_itr0_3e-05_all_16_02_2022-20_43_00
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: 0.1626
- Precision: 0.3811
- Recall: 0.3865
- F1: 0.3838
- Accuracy: 0.9482
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: 3e-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 | 0.3697 | 0.0933 | 0.2235 | 0.1317 | 0.8259 |
| No log | 2.0 | 76 | 0.3193 | 0.1266 | 0.2948 | 0.1771 | 0.8494 |
| No log | 3.0 | 114 | 0.3025 | 0.1606 | 0.3160 | 0.2130 | 0.8540 |
| No log | 4.0 | 152 | 0.2978 | 0.1867 | 0.3449 | 0.2422 | 0.8605 |
| No log | 5.0 | 190 | 0.2984 | 0.1706 | 0.3507 | 0.2295 | 0.8551 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3