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# t5-small-finetuned-xsum

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the scitldr dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8686
- Rouge1: 24.7942
- Rouge2: 7.8227
- Rougel: 21.2018
- Rougelsum: 21.2779
- Gen Len: 18.4297

## 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: 2e-05
- 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: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 125  | 4.1327          | 23.5028 | 7.9229 | 19.2335 | 19.2839   | 18.5024 |
| No log        | 2.0   | 250  | 4.0197          | 23.4862 | 7.3941 | 19.1734 | 19.2273   | 18.4475 |
| No log        | 3.0   | 375  | 3.9659          | 24.0596 | 7.6225 | 20.2649 | 20.3197   | 18.2375 |
| 4.2188        | 4.0   | 500  | 3.9302          | 24.323  | 7.9627 | 20.7527 | 20.8616   | 18.1826 |
| 4.2188        | 5.0   | 625  | 3.9060          | 24.7138 | 7.9075 | 21.1786 | 21.2552   | 18.1939 |
| 4.2188        | 6.0   | 750  | 3.8900          | 24.696  | 7.7986 | 21.161  | 21.2083   | 18.2342 |
| 4.2188        | 7.0   | 875  | 3.8801          | 24.8363 | 7.852  | 21.2452 | 21.3039   | 18.3473 |
| 3.991         | 8.0   | 1000 | 3.8736          | 24.8537 | 7.9099 | 21.2259 | 21.3141   | 18.3845 |
| 3.991         | 9.0   | 1125 | 3.8700          | 24.7938 | 7.8088 | 21.1743 | 21.2603   | 18.4233 |
| 3.991         | 10.0  | 1250 | 3.8686          | 24.7942 | 7.8227 | 21.2018 | 21.2779   | 18.4297 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["scitldr"], "metrics": ["rouge"], "model-index": [{"name": "t5-small-finetuned-xsum", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "scitldr", "type": "scitldr", "config": "Abstract", "split": "validation", "args": "Abstract"}, "metrics": [{"type": "rouge", "value": 24.7942, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer dataset:scitldr license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-scitldr #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-finetuned-xsum
=======================


This model is a fine-tuned version of t5-small on the scitldr dataset.
It achieves the following results on the evaluation set:


* Loss: 3.8686
* Rouge1: 24.7942
* Rouge2: 7.8227
* Rougel: 21.2018
* Rougelsum: 21.2779
* Gen Len: 18.4297


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: 2e-05
* 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: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* 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: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-scitldr #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* 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: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.12.1