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---
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: bert-base-cased-samsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: test
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 34.9636
---
<!-- 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. -->
# bert-base-cased-samsum
This model is a fine-tuned version of [](https://huggingface.co/) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7369
- Rouge1: 34.9636
- Rouge2: 10.6358
- Rougel: 27.6003
- Rougelsum: 30.9654
- Gen Len: 17.6020
## 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: 36
- eval_batch_size: 36
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log | 1.0 | 410 | 2.9218 | 29.2936 | 7.4008 | 23.9609 | 26.3194 | 17.2332 |
| 2.6834 | 2.0 | 820 | 2.7635 | 31.9826 | 8.9758 | 26.1311 | 28.7458 | 16.9866 |
| 2.3529 | 3.0 | 1230 | 2.7369 | 34.9636 | 10.6358 | 27.6003 | 30.9654 | 17.6020 |
| 1.9608 | 4.0 | 1640 | 2.7711 | 35.8322 | 11.3676 | 29.0276 | 32.2881 | 16.9133 |
| 1.6459 | 5.0 | 2050 | 2.7832 | 36.8688 | 11.8883 | 29.3721 | 32.8683 | 17.0879 |
| 1.6459 | 6.0 | 2460 | 2.8334 | 36.489 | 11.5372 | 29.2263 | 32.5406 | 17.8901 |
| 1.3791 | 7.0 | 2870 | 2.8767 | 37.0743 | 11.8554 | 29.4063 | 32.7543 | 17.6093 |
| 1.1687 | 8.0 | 3280 | 2.9232 | 37.2 | 11.8723 | 29.5194 | 32.9481 | 17.6581 |
| 1.0249 | 9.0 | 3690 | 2.9456 | 37.1872 | 12.0958 | 29.621 | 33.0073 | 17.8840 |
| 0.9259 | 10.0 | 4100 | 2.9719 | 37.1213 | 12.1068 | 29.5138 | 33.0372 | 17.8278 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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