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finetuned_token_itr0_0.0002_webDiscourse_16_02_2022-21_00_50
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: 0.5530
- Precision: 0.0044
- Recall: 0.0182
- F1: 0.0071
- Accuracy: 0.7268
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 | 10 | 0.7051 | 0.0645 | 0.0323 | 0.0430 | 0.4465 |
| No log | 2.0 | 20 | 0.6928 | 0.0476 | 0.0161 | 0.0241 | 0.5546 |
| No log | 3.0 | 30 | 0.6875 | 0.0069 | 0.0484 | 0.0120 | 0.5533 |
| No log | 4.0 | 40 | 0.6966 | 0.0064 | 0.0323 | 0.0107 | 0.5832 |
| No log | 5.0 | 50 | 0.7093 | 0.0061 | 0.0323 | 0.0102 | 0.5742 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3
