README.md

metadata

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... ;)

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

This model is a fine-tuned version of 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