transformers tensorboard safetensors gpt2 text-classification generated_from_trainer dataset:stanfordnlp/snli base_model:openai-community/gpt2 base_model:finetune:openai-community/gpt2 license:mit model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: openai-community/gpt2
datasets:
- stanfordnlp/snli
license: mit
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: gpt2-lora-592K-snli-model2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: snli
      type: stanfordnlp/snli
    metrics:
    - type: accuracy
      value: 0.7926234505181874
      name: Accuracy
---

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# gpt2-lora-592K-snli-model2

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: 0.5249
- Accuracy: 0.7926

## 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: 10
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7231        | 1.0   | 2146 | 0.5854          | 0.7600   |
| 0.6412        | 2.0   | 4292 | 0.5355          | 0.7867   |
| 0.6266        | 3.0   | 6438 | 0.5249          | 0.7926   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
