distilbert-base-uncased-finetuned-mnli
This model is a fine-tuned version of distilbert-base-uncased on the Amazon KDD Cup dataset. It achieves the following results on the evaluation set:
- Loss: 0.6295
- Accuracy: 0.759
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: 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.661 | 1.0 | 17851 | 0.6604 | 0.7434 |
| 0.5822 | 2.0 | 35702 | 0.6295 | 0.759 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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Model tree for yahid/distilbert-base-uncased-finetuned-amazon-kdd
Base model
distilbert/distilbert-base-uncased