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finetuned_token_itr0_0.0002_all_16_02_2022-20_45_27
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: 0.1500
- Precision: 0.4739
- Recall: 0.5250
- F1: 0.4981
- Accuracy: 0.9551
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 | 0.3183 | 0.2024 | 0.2909 | 0.2387 | 0.8499 |
No log | 2.0 | 76 | 0.3092 | 0.2909 | 0.4181 | 0.3431 | 0.8548 |
No log | 3.0 | 114 | 0.2928 | 0.2923 | 0.4855 | 0.3650 | 0.8647 |
No log | 4.0 | 152 | 0.3098 | 0.2832 | 0.4605 | 0.3507 | 0.8641 |
No log | 5.0 | 190 | 0.3120 | 0.2470 | 0.4374 | 0.3157 | 0.8654 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3