metadata
base_model: google/pegasus-large
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: samsum_5535_pegasus-large
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: validation
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 0.5273
samsum_5535_pegasus-large
This model is a fine-tuned version of google/pegasus-large on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 0.4847
- Rouge1: 0.5273
- Rouge2: 0.2794
- Rougel: 0.4378
- Rougelsum: 0.4376
- Gen Len: 22.6565
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: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.5641 | 4.34 | 500 | 0.5145 | 0.5069 | 0.2664 | 0.4229 | 0.4228 | 21.187 |
| 0.4689 | 8.69 | 1000 | 0.4847 | 0.5273 | 0.2794 | 0.4378 | 0.4376 | 22.6565 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0