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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-finetuned
results: []
datasets:
- stanfordnlp/sst2
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-finetuned
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [sst2 dataset](https://huggingface.co/datasets/stanfordnlp/sst2).
It achieves the following results on the evaluation set:
- Loss: 0.4770
- Accuracy: 0.9014
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.227 | 1.0 | 8419 | 0.4213 | 0.8819 |
| 0.1453 | 2.0 | 16838 | 0.4544 | 0.8922 |
| 0.0816 | 3.0 | 25257 | 0.4770 | 0.9014 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2