complete: train_size: {train_size}, batch_size: {batch_size}, per_epoch_steps: {per_epoch_steps}, epochs: {epochs}, epoch_total_steps: {epoch_total_steps}
f9eaa6a
verified
metadata
license: mit
base_model: openai-community/gpt2-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: gpt2-large-coedit
results: []
gpt2-large-coedit
This model is a fine-tuned version of 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