base_model: google/pegasus-cnn_dailymail | |
tags: | |
- generated_from_trainer | |
datasets: | |
- samsum | |
model-index: | |
- name: pegasus-samsum | |
results: [] | |
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# pegasus-samsum | |
This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the samsum dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 1.4858 | |
## 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: 1 | |
- eval_batch_size: 1 | |
- seed: 42 | |
- gradient_accumulation_steps: 16 | |
- total_train_batch_size: 16 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- lr_scheduler_warmup_steps: 500 | |
- num_epochs: 1 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | | |
|:-------------:|:-----:|:----:|:---------------:| | |
| 1.6297 | 0.54 | 500 | 1.4858 | | |
### Framework versions | |
- Transformers 4.31.0 | |
- Pytorch 2.0.1+cu118 | |
- Datasets 2.13.1 | |
- Tokenizers 0.13.3 | |