metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
base_model: bert-base-uncased
model-index:
- name: bert-base-sst2
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: glue
type: glue
config: sst2
split: train
args: sst2
metrics:
- type: accuracy
value: 0.9036697247706422
name: Accuracy
bert-base-sst2
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3735
- Accuracy: 0.9037
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: 16
- eval_batch_size: 16
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.243 | 1.0 | 4210 | 0.3735 | 0.9037 |
| 0.1557 | 2.0 | 8420 | 0.3907 | 0.8922 |
| 0.1248 | 3.0 | 12630 | 0.3690 | 0.8945 |
| 0.1017 | 4.0 | 16840 | 0.5466 | 0.8830 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1