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# 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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["samsum"], "metrics": ["rouge"], "widget": [{"text": "Sid: Wanna catch a movie?\nAnnie: sure what do you have in mind?\nSid; the Aquaman? :D\nAnnie: haha isn't it a bit childish\nSid: noooooo I mean yes but it's the highest grossing movie this week\nAnnie: seriously?\nSid: yeah?\nAnnie: okay let's see what the fuss is all about"}, {"text": "Manu: What are you doing?\nJulien: CTO tasks\nManu: Sounds boring...\nJulien: yes you know :S\nManu: why don't you come home to see my pets?\nJulien: sounds like a plan!!!\nManu: so, are you coming?\nJulien: it seems so... ;)"}], "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": 46.1297, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard switch_transformers text2text-generation generated_from_trainer dataset:samsum license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #switch_transformers #text2text-generation #generated_from_trainer #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

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



### Framework versions


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



### 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 ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.0+cu116
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #switch_transformers #text2text-generation #generated_from_trainer #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.0+cu116
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #switch_transformers #text2text-generation #generated_from_trainer #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


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