metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
model-index:
- name: outputs
results: []
outputs
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: 0.0122
- F1 Micro: 0.6194
- F1 Macro: 0.0119
- Precision Micro: 0.7934
- Recall Micro: 0.5080
- Subset Accuracy: 0.3677
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Precision Micro | Recall Micro | Subset Accuracy |
|---|---|---|---|---|---|---|---|---|
| 0.0129 | 1.0 | 1025 | 0.0122 | 0.6194 | 0.0119 | 0.7934 | 0.5080 | 0.3677 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Tokenizers 0.21.1