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---
license: mit
base_model: openai-community/gpt2
tags:
- generated_from_trainer
datasets:
- stanfordnlp/snli
metrics:
- accuracy
model-index:
- name: gpt2-lora-592K-snli-model3
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: snli
type: stanfordnlp/snli
metrics:
- name: Accuracy
type: accuracy
value: 0.7878479983743142
---
<!-- 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-lora-592K-snli-model3
This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the snli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5303
- Accuracy: 0.7878
## 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: 256
- eval_batch_size: 128
- seed: 74
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7313 | 1.0 | 2146 | 0.5860 | 0.7602 |
| 0.6559 | 2.0 | 4292 | 0.5387 | 0.7834 |
| 0.6367 | 3.0 | 6438 | 0.5303 | 0.7878 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|