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finetuned_token_itr0_0.0002_essays_16_02_2022-21_04_02
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: 0.2158
- Precision: 0.5814
- Recall: 0.7073
- F1: 0.6382
- Accuracy: 0.9248
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 | 11 | 0.3920 | 0.4392 | 0.6069 | 0.5096 | 0.8593 |
No log | 2.0 | 22 | 0.3304 | 0.4282 | 0.6260 | 0.5085 | 0.8672 |
No log | 3.0 | 33 | 0.3361 | 0.4840 | 0.6336 | 0.5488 | 0.8685 |
No log | 4.0 | 44 | 0.3258 | 0.5163 | 0.6641 | 0.5810 | 0.8722 |
No log | 5.0 | 55 | 0.3472 | 0.5192 | 0.6718 | 0.5857 | 0.8743 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3