metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: sst2
split: train
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.9025229357798165
distilbert-base-uncased-finetuned-sst2
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.2823
- 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: 2e-05
- train_batch_size: 512
- eval_batch_size: 512
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 132 | 0.2528 | 0.8933 |
| No log | 2.0 | 264 | 0.2675 | 0.8979 |
| No log | 3.0 | 396 | 0.2823 | 0.9025 |
| 0.1898 | 4.0 | 528 | 0.2986 | 0.8968 |
| 0.1898 | 5.0 | 660 | 0.3029 | 0.9002 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1