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---
license: mit
base_model: gpt2-medium
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gmra_model_gpt2-medium_14082023T134929
results: []
---
<!-- 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. -->
# gmra_model_gpt2-medium_14082023T134929
This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3831
- Accuracy: 0.9438
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 284 | 0.2626 | 0.9069 |
| 0.3464 | 2.0 | 568 | 0.2263 | 0.9262 |
| 0.3464 | 3.0 | 852 | 0.2545 | 0.9394 |
| 0.1022 | 4.0 | 1137 | 0.2577 | 0.9464 |
| 0.1022 | 5.0 | 1421 | 0.3485 | 0.9420 |
| 0.0292 | 6.0 | 1705 | 0.3445 | 0.9429 |
| 0.0292 | 7.0 | 1989 | 0.3127 | 0.9464 |
| 0.0125 | 8.0 | 2274 | 0.4068 | 0.9411 |
| 0.0085 | 9.0 | 2558 | 0.3853 | 0.9438 |
| 0.0085 | 9.99 | 2840 | 0.3831 | 0.9438 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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