metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-sst2
results: []
datasets:
- stanfordnlp/sst2
distilbert-base-uncased-finetuned-sst2
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: 0.3372
- Accuracy: 0.9025
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.1777 | 1.0 | 1053 | 0.2593 | 0.9014 |
| 0.1042 | 2.0 | 2106 | 0.3127 | 0.8968 |
| 0.0575 | 3.0 | 3159 | 0.3372 | 0.9025 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cpu
- Datasets 3.5.0
- Tokenizers 0.21.0