metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-finetuned
results: []
datasets:
- stanfordnlp/sst2
distilbert-finetuned
This model is a fine-tuned version of distilbert-base-uncased on the sst2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4770
- Accuracy: 0.9014
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.227 | 1.0 | 8419 | 0.4213 | 0.8819 |
| 0.1453 | 2.0 | 16838 | 0.4544 | 0.8922 |
| 0.0816 | 3.0 | 25257 | 0.4770 | 0.9014 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2