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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
base_model: google/switch-base-8
model-index:
- name: switch-base-8-finetuned-samsum
results:
- task:
type: text2text-generation
name: Sequence-to-sequence Language Modeling
dataset:
name: samsum
type: samsum
config: samsum
split: train
args: samsum
metrics:
- type: rouge
value: 46.5651
name: Rouge1
---
<!-- 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. -->
# switch-base-8-finetuned-samsum
This model is a fine-tuned version of [google/switch-base-8](https://huggingface.co/google/switch-base-8) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4606
- Rouge1: 46.5651
- Rouge2: 23.2378
- Rougel: 39.4484
- Rougelsum: 43.1011
- Gen Len: 17.0183
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.8829 | 1.0 | 3683 | 1.5154 | 46.3805 | 23.0982 | 39.0612 | 43.0142 | 17.6296 |
| 1.6207 | 2.0 | 7366 | 1.4578 | 47.7434 | 24.9471 | 40.6481 | 44.351 | 17.2066 |
| 1.442 | 3.0 | 11049 | 1.4360 | 47.6903 | 24.9954 | 40.713 | 44.3487 | 17.0501 |
| 1.3103 | 4.0 | 14732 | 1.4396 | 48.4517 | 25.7725 | 41.5212 | 45.1211 | 16.9071 |
| 1.2393 | 5.0 | 18415 | 1.4445 | 48.4002 | 25.8727 | 41.5361 | 45.0467 | 16.9804 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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