metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-finetuned-assign4
results: []
distilbert-finetuned-assign4
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: 0.8010
- Accuracy: 0.9171
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: 48
- eval_batch_size: 48
- 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 |
|---|---|---|---|---|
| 4.316 | 1.0 | 318 | 3.3201 | 0.7303 |
| 2.6667 | 2.0 | 636 | 1.9148 | 0.8448 |
| 1.5862 | 3.0 | 954 | 1.1892 | 0.8926 |
| 1.045 | 4.0 | 1272 | 0.8876 | 0.9129 |
| 0.8245 | 5.0 | 1590 | 0.8010 | 0.9171 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1