metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: topic_classification
results: []
topic_classification
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: 2.3890
- Model Preparation Time: 0.0033
- Accuracy: 0.15
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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
- training_steps: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy |
|---|---|---|---|---|---|
| No log | 0.3846 | 5 | 2.3190 | 0.0033 | 0.15 |
| No log | 0.7692 | 10 | 2.3612 | 0.0033 | 0.15 |
| No log | 1.1538 | 15 | 2.3687 | 0.0033 | 0.15 |
| No log | 1.5385 | 20 | 2.3841 | 0.0033 | 0.15 |
| No log | 1.9231 | 25 | 2.3890 | 0.0033 | 0.15 |
| No log | 2.3077 | 30 | 2.3890 | 0.0033 | 0.15 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0