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---
license: mit
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: gpt2-imdb-sentiment-classifier
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.9394
---
<!-- 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. -->
# gpt2-imdb-sentiment-classifier
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1703
- Accuracy: 0.9394
## Model description
More information needed
## Intended uses & limitations
This is comparable to [distilbert-imdb](https://huggingface.co/lvwerra/distilbert-imdb) and trained with exactly the same [script](https://huggingface.co/lvwerra/distilbert-imdb/blob/main/distilbert-imdb-training.ipynb)
It achieves slightly lower loss (0.1703 vs 0.1903) and slightly higher accuracy (0.9394 vs 0.928)
## 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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1967 | 1.0 | 1563 | 0.1703 | 0.9394 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.12.1
|