finetuned_token_itr0_0.0002_all_16_02_2022-20_30_01
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: 0.1577
- Precision: 0.4469
- Recall: 0.5280
- F1: 0.4841
- Accuracy: 0.9513
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 | 0.3553 | 0.1068 | 0.0810 | 0.0922 | 0.8412 |
| No log | 2.0 | 76 | 0.2812 | 0.2790 | 0.4017 | 0.3293 | 0.8684 |
| No log | 3.0 | 114 | 0.2793 | 0.3086 | 0.4586 | 0.3689 | 0.8747 |
| No log | 4.0 | 152 | 0.2766 | 0.3057 | 0.4190 | 0.3535 | 0.8763 |
| No log | 5.0 | 190 | 0.2805 | 0.2699 | 0.4845 | 0.3467 | 0.8793 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3