---
license: mit
base_model: openai-community/gpt2-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: gpt2-large-coedit
  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. -->

# gpt2-large-coedit

This model is a fine-tuned version of [openai-community/gpt2-large](https://huggingface.co/openai-community/gpt2-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9215
- Rouge1: 0.4818
- Rouge2: 0.3649
- Rougel: 0.4555
- Rougelsum: 0.4643
- Sacreblue: 19.1714
- Memory Used: 68475.5
- Cuda Allocated: 3082.6328
- Cuda Reserved: 61060.0
- Ram Usage: 13976.5117
- Em: 0.0
- Gen Len: 82.1798

## 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: 150
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 600
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Sacreblue | Memory Used | Cuda Allocated | Cuda Reserved | Ram Usage  | Em  | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:---------:|:-----------:|:--------------:|:-------------:|:----------:|:---:|:-------:|
| 0.8724        | 0.47  | 50   | 1.0274          | 0.4653 | 0.3509 | 0.4382 | 0.4459    | 19.0412   | 68475.5     | 3082.605       | 61060.0       | 5708.957   | 0.0 | 82.0895 |
| 0.7407        | 0.94  | 100  | 0.9499          | 0.4825 | 0.3651 | 0.4557 | 0.4656    | 19.2975   | 68475.5     | 3082.6152      | 61060.0       | 13842.9336 | 0.0 | 81.3952 |
| 0.6964        | 1.41  | 150  | 0.9318          | 0.4783 | 0.3627 | 0.452  | 0.4605    | 19.418    | 68475.5     | 3082.6182      | 61060.0       | 13958.2773 | 0.0 | 81.0295 |
| 0.6846        | 1.88  | 200  | 0.9215          | 0.4818 | 0.3649 | 0.4555 | 0.4643    | 19.1714   | 68475.5     | 3082.6328      | 61060.0       | 13976.5117 | 0.0 | 82.1798 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2