---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: switch-base-8-finetuned-samsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: train
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 46.1297

widget:
 - text: |-
      Sid: Wanna catch a movie?
      Annie: sure what do you have in mind?
      Sid; the Aquaman? :D
      Annie: haha isn't it a bit childish
      Sid: noooooo I mean yes but it's the highest grossing movie this week
      Annie: seriously?
      Sid: yeah?
      Annie: okay let's see what the fuss is all about

 - text: |-
     Manu: What are you doing?
     Julien: CTO tasks
     Manu: Sounds boring...
     Julien: yes you know :S
     Manu: why don't you come home to see my pets?
     Julien: sounds like a plan!!!
     Manu: so, are you coming?
     Julien: it seems so... ;)
---

<!-- 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 Transformer (base-8) fine-tuned on samsum dataset for conversation summarization

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: 1.4614
- Rouge1: 46.1297
- Rouge2: 22.9128
- Rougel: 39.153
- Rougelsum: 42.8502
- Gen Len: 16.9719

## 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: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.8874        | 1.0   | 3683  | 1.5210          | 45.7651 | 22.9379 | 38.8554 | 42.6269   | 17.2482 |
| 1.6301        | 2.0   | 7366  | 1.4628          | 47.2719 | 24.8976 | 40.3913 | 43.9285   | 16.8362 |
| 1.4326        | 3.0   | 11049 | 1.4402          | 47.8275 | 25.2262 | 40.617  | 44.2948   | 16.9523 |
| 1.2992        | 4.0   | 14732 | 1.4489          | 48.393  | 25.3888 | 40.9534 | 44.797    | 17.1504 |
| 1.2259        | 5.0   | 18415 | 1.4495          | 49.2186 | 26.312  | 41.721  | 45.5087   | 17.1956 |
| 1.1477        | 6.0   | 22098 | 1.4610          | 49.0018 | 26.3474 | 41.5217 | 45.4081   | 17.0782 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2