---
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: switch-base-32-samsum-ba16-lr1e-04-top-4-choose-1-res-phase2-budget3-dim1
  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: 50.511
---

<!-- 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-32-samsum-ba16-lr1e-04-top-4-choose-1-res-phase2-budget3-dim1

This model was trained from scratch on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8163
- Rouge1: 50.511
- Rouge2: 26.0947
- Rougel: 42.4175
- Rougelsum: 46.4756
- Gen Len: 20.522

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.2114        | 0.5429 | 500  | 1.6695          | 49.8655 | 25.6608 | 42.0018 | 46.1475   | 20.4132 |
| 1.1553        | 1.0858 | 1000 | 1.7089          | 50.2875 | 25.9243 | 42.157  | 46.4898   | 22.3178 |
| 1.1419        | 1.6287 | 1500 | 1.6890          | 50.7227 | 26.5404 | 42.6219 | 46.9542   | 21.0575 |
| 1.0082        | 2.1716 | 2000 | 1.7140          | 51.0857 | 26.9422 | 42.9033 | 47.4713   | 21.6002 |
| 1.057         | 2.7144 | 2500 | 1.7156          | 50.6415 | 26.6621 | 42.6293 | 46.728    | 21.6333 |
| 0.9098        | 3.2573 | 3000 | 1.7776          | 51.1518 | 27.178  | 43.2364 | 47.3776   | 21.2433 |
| 0.993         | 3.8002 | 3500 | 1.7702          | 50.9856 | 26.6895 | 42.0314 | 46.9763   | 22.6919 |
| 0.8361        | 4.3431 | 4000 | 1.8436          | 50.4271 | 25.8178 | 42.3022 | 46.5182   | 21.9022 |
| 0.9078        | 4.8860 | 4500 | 1.8163          | 50.511  | 26.0947 | 42.4175 | 46.4756   | 20.522  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1