20% of the training data
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum-wei1
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 27.5875
---

<!-- 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. -->

# t5-small-finetuned-xsum-wei1

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5287
- Rouge1: 27.5875
- Rouge2: 7.4083
- Rougel: 21.5654
- Rougelsum: 21.5716
- Gen Len: 18.8205

## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.7677        | 1.0   | 3401 | 2.5441          | 27.4235 | 7.2208 | 21.3535 | 21.3636   | 18.8311 |
| 2.735         | 2.0   | 6802 | 2.5287          | 27.5875 | 7.4083 | 21.5654 | 21.5716   | 18.8205 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3

{}
transformers pytorch tensorboard t5 text2text-generation autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

20% of the training data
------------------------


license: apache-2.0
tags:


* generated\_from\_trainer
datasets:
* xsum
metrics:
* rouge
model-index:
* name: t5-small-finetuned-xsum-wei1
results:
	+ task:
	name: Sequence-to-sequence Language Modeling
	type: text2text-generation
	dataset:
	name: xsum
	type: xsum
	args: default
	metrics:
		- name: Rouge1
		type: rouge
		value: 27.5875




---


t5-small-finetuned-xsum-wei1
============================


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


* Loss: 2.5287
* Rouge1: 27.5875
* Rouge2: 7.4083
* Rougel: 21.5654
* Rougelsum: 21.5716
* Gen Len: 18.8205


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: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.14.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.14.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #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: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.14.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #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: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.14.0
* Tokenizers 0.10.3