kritika_distilbert_model
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: 0.5545
- Accuracy: 0.8424
- F1: 0.8424
- Precision: 0.8426
- Recall: 0.8424
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4212 | 1.0 | 534 | 0.4236 | 0.8189 | 0.8172 | 0.8313 | 0.8189 |
| 0.253 | 2.0 | 1068 | 0.4338 | 0.8443 | 0.8442 | 0.8446 | 0.8443 |
| 0.1618 | 3.0 | 1602 | 0.5545 | 0.8424 | 0.8424 | 0.8426 | 0.8424 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for kritika5/kritika_distilbert_model
Base model
distilbert/distilbert-base-uncased