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finetuned_token_itr0_2e-05_essays_16_02_2022-21_01_51
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: 0.2525
- Precision: 0.3997
- Recall: 0.5117
- F1: 0.4488
- Accuracy: 0.9115
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 | 11 | 0.4652 | 0.1528 | 0.3588 | 0.2144 | 0.7851 |
No log | 2.0 | 22 | 0.3646 | 0.2913 | 0.4847 | 0.3639 | 0.8521 |
No log | 3.0 | 33 | 0.3453 | 0.3789 | 0.5611 | 0.4523 | 0.8708 |
No log | 4.0 | 44 | 0.3270 | 0.3673 | 0.5496 | 0.4404 | 0.8729 |
No log | 5.0 | 55 | 0.3268 | 0.4011 | 0.5725 | 0.4717 | 0.8760 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3