distilbert-base-uncased-finetuned-m_avoid_harm_seler
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3246
- Accuracy: 0.865
- F1: 0.9036
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: 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 |
|---|---|---|---|---|---|
| 0.6332 | 1.0 | 26 | 0.6646 | 0.52 | 0.6500 |
| 0.5699 | 2.0 | 52 | 0.5403 | 0.73 | 0.8152 |
| 0.4384 | 3.0 | 78 | 0.4396 | 0.78 | 0.8493 |
| 0.3301 | 4.0 | 104 | 0.3237 | 0.86 | 0.9004 |
| 0.2949 | 5.0 | 130 | 0.3246 | 0.865 | 0.9036 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1
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Model tree for Gregorig/distilbert-base-uncased-finetuned-m_avoid_harm_seler
Base model
distilbert/distilbert-base-uncased