liar_binaryclassifier_distilbert_cased
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6381
- Accuracy: 0.6421
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: 3e-06
- train_batch_size: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|
| 0.683 | 1.0 | 461 | 0.6589 | 0.6030 |
| 0.6441 | 2.0 | 922 | 0.6351 | 0.6356 |
| 0.6179 | 3.0 | 1383 | 0.6339 | 0.6291 |
| 0.6011 | 4.0 | 1844 | 0.6351 | 0.6399 |
| 0.5897 | 5.0 | 2305 | 0.6381 | 0.6421 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for vishalk4u/liar_binaryclassifier_distilbert_cased
Base model
distilbert/distilbert-base-cased