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# Switch Transformer (base-16) fine-tuned om samsum for conversation summarization

This model is a fine-tuned version of [google/switch-base-16](https://huggingface.co/google/switch-base-16) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4434
- Rouge1: 47.2139
- Rouge2: 23.3399
- Rougel: 39.8364
- Rougelsum: 43.2592
- Gen Len: 16.9194

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.846         | 1.0   | 3683  | 1.4857          | 45.9134 | 22.4258 | 38.9716 | 42.6169   | 17.0623 |
| 1.5734        | 2.0   | 7366  | 1.4346          | 47.574  | 24.2967 | 40.3749 | 44.2636   | 17.3790 |
| 1.38          | 3.0   | 11049 | 1.4277          | 47.9915 | 24.9077 | 40.658  | 44.5301   | 17.1406 |
| 1.2388        | 4.0   | 14732 | 1.4223          | 48.3444 | 25.4061 | 41.2776 | 45.0434   | 16.9254 |
| 1.1629        | 5.0   | 18415 | 1.4372          | 48.5991 | 25.5464 | 41.3726 | 45.0784   | 16.9890 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.7.1
- 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"}], "model-index": [{"name": "switch-base-16-finetuned-samsum", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "samsum", "type": "samsum", "config": "samsum", "split": "validation", "args": "samsum"}, "metrics": [{"type": "rouge", "value": 47.2139, "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-16) fine-tuned om samsum for conversation summarization
================================================================================


This model is a fine-tuned version of google/switch-base-16 on the samsum dataset.
It achieves the following results on the evaluation set:


* Loss: 1.4434
* Rouge1: 47.2139
* Rouge2: 23.3399
* Rougel: 39.8364
* Rougelsum: 43.2592
* Gen Len: 16.9194


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



### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.7.1
* 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: 5 ### Training results ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.7.1
* 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: 5 ### Training results ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.7.1
* 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: 5### Training results### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.7.1
* Tokenizers 0.13.2