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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model_index:
- name: bert-base-uncased-finetuned-sst2
results:
- dataset:
name: glue
type: glue
args: sst2
metric:
name: Accuracy
type: accuracy
value: 0.930045871559633
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-uncased-finetuned-sst2
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2485
- Accuracy: 0.9300
## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1662 | 1.0 | 2105 | 0.2485 | 0.9300 |
| 0.1102 | 2.0 | 4210 | 0.2777 | 0.9266 |
| 0.0835 | 3.0 | 6315 | 0.3368 | 0.9232 |
| 0.0529 | 4.0 | 8420 | 0.3310 | 0.9255 |
| 0.035 | 5.0 | 10525 | 0.3855 | 0.9278 |
### Framework versions
- Transformers 4.9.1
- Pytorch 1.8.1
- Datasets 1.11.0
- Tokenizers 0.10.1
|