|
|
--- |
|
|
library_name: transformers |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: gpt22gpt2-gpt2-medium-cnn-dailymail-seed42_std_paper |
|
|
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. --> |
|
|
|
|
|
# gpt22gpt2-gpt2-medium-cnn-dailymail-seed42_std_paper |
|
|
|
|
|
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: nan |
|
|
- Rouge1: 0.0 |
|
|
- Rouge2: 0.0 |
|
|
- Rougel: 0.0 |
|
|
- Rougelsum: 0.0 |
|
|
|
|
|
## 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: 5e-05 |
|
|
- train_batch_size: 8 |
|
|
- eval_batch_size: 16 |
|
|
- 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 |
|
|
- lr_scheduler_warmup_steps: 1000 |
|
|
- num_epochs: 3.0 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|
|:-------------:|:------:|:-----:|:---------------:|:------:|:------:|:------:|:---------:| |
|
|
| 2.8351 | 0.2229 | 2000 | 2.6756 | 0.2177 | 0.0446 | 0.1396 | 0.2009 | |
|
|
| 2.6697 | 0.4458 | 4000 | 2.5354 | 0.2466 | 0.0595 | 0.1537 | 0.2261 | |
|
|
| 2.5729 | 0.6687 | 6000 | 2.4532 | 0.2635 | 0.0672 | 0.1622 | 0.2443 | |
|
|
| 2.5091 | 0.8916 | 8000 | 2.3906 | 0.2551 | 0.0657 | 0.1576 | 0.2333 | |
|
|
| 0.0 | 1.1145 | 10000 | nan | 0.0 | 0.0 | 0.0 | 0.0 | |
|
|
| 0.0 | 1.3374 | 12000 | nan | 0.0 | 0.0 | 0.0 | 0.0 | |
|
|
| 0.0 | 1.5603 | 14000 | nan | 0.0 | 0.0 | 0.0 | 0.0 | |
|
|
| 0.0 | 1.7832 | 16000 | nan | 0.0 | 0.0 | 0.0 | 0.0 | |
|
|
| 0.0 | 2.0061 | 18000 | nan | 0.0 | 0.0 | 0.0 | 0.0 | |
|
|
| 0.0 | 2.2290 | 20000 | nan | 0.0 | 0.0 | 0.0 | 0.0 | |
|
|
| 0.0 | 2.4519 | 22000 | nan | 0.0 | 0.0 | 0.0 | 0.0 | |
|
|
| 0.0 | 2.6748 | 24000 | nan | 0.0 | 0.0 | 0.0 | 0.0 | |
|
|
| 0.0 | 2.8977 | 26000 | nan | 0.0 | 0.0 | 0.0 | 0.0 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.44.2 |
|
|
- Pytorch 2.4.0 |
|
|
- Datasets 2.21.0 |
|
|
- Tokenizers 0.19.1 |
|
|
|
