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---
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
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.908256880733945
---
<!-- 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. -->
# distilbert-base-uncased-finetuned-sst2
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4101
- Accuracy: 0.9083
## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1843 | 1.0 | 4210 | 0.3040 | 0.9037 |
| 0.1253 | 2.0 | 8420 | 0.3577 | 0.8968 |
| 0.0818 | 3.0 | 12630 | 0.4101 | 0.9083 |
| 0.0676 | 4.0 | 16840 | 0.4326 | 0.8991 |
| 0.0455 | 5.0 | 21050 | 0.5258 | 0.9002 |
### Framework versions
- Transformers 4.12.0
- Pytorch 1.8.1+cpu
- Datasets 2.4.0
- Tokenizers 0.10.3