finetuned_token_2e-05_all_16_02_2022-15_43_42
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: 0.1750
- Precision: 0.3286
- Recall: 0.3334
- F1: 0.3310
- Accuracy: 0.9447
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 | 0.3355 | 0.0975 | 0.2358 | 0.1380 | 0.8361 |
| No log | 2.0 | 76 | 0.3177 | 0.1359 | 0.2709 | 0.1810 | 0.8398 |
| No log | 3.0 | 114 | 0.3000 | 0.1542 | 0.3043 | 0.2047 | 0.8471 |
| No log | 4.0 | 152 | 0.3033 | 0.1589 | 0.3060 | 0.2091 | 0.8434 |
| No log | 5.0 | 190 | 0.3029 | 0.1629 | 0.3110 | 0.2138 | 0.8447 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3