finetuned_token_itr0_2e-05_all_16_02_2022-20_40_28
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: 0.1736
- Precision: 0.3358
- Recall: 0.3447
- F1: 0.3402
- Accuracy: 0.9452
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 | 0.3058 | 0.1200 | 0.2102 | 0.1528 | 0.8629 |
| No log | 2.0 | 76 | 0.2488 | 0.1605 | 0.2774 | 0.2034 | 0.9003 |
| No log | 3.0 | 114 | 0.2296 | 0.1947 | 0.2880 | 0.2324 | 0.9057 |
| No log | 4.0 | 152 | 0.2208 | 0.2201 | 0.2986 | 0.2534 | 0.9113 |
| No log | 5.0 | 190 | 0.2235 | 0.2110 | 0.3039 | 0.2491 | 0.9101 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3