finetuned_sentence_itr0_0.0002_essays_27_02_2022-19_33_10
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: 0.3358
- Accuracy: 0.8688
- F1: 0.9225
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: 64
- eval_batch_size: 64
- 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 | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 81 | 0.4116 | 0.8382 | 0.9027 |
No log | 2.0 | 162 | 0.4360 | 0.8382 | 0.8952 |
No log | 3.0 | 243 | 0.5719 | 0.8382 | 0.8995 |
No log | 4.0 | 324 | 0.7251 | 0.8493 | 0.9021 |
No log | 5.0 | 405 | 0.8384 | 0.8456 | 0.9019 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3
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