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
| 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 | |