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# longt5-mediasum

This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0129

## 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: 12
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.66          | 1.0   | 1667 | 2.0643          |
| 2.472         | 2.0   | 3334 | 2.0241          |
| 2.3574        | 3.0   | 5001 | 2.0129          |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0a0+17540c5
- Datasets 2.3.2
- Tokenizers 0.12.1

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transformers pytorch safetensors longt5 text2text-generation generated_from_trainer summarization base_model:google/long-t5-tglobal-base license:cc-by-nc-sa-4.0 model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #safetensors #longt5 #text2text-generation #generated_from_trainer #summarization #base_model-google/long-t5-tglobal-base #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

longt5-mediasum
===============


This model is a fine-tuned version of google/long-t5-tglobal-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0129


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: 12
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3.0


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0a0+17540c5
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 12
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0a0+17540c5
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #safetensors #longt5 #text2text-generation #generated_from_trainer #summarization #base_model-google/long-t5-tglobal-base #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 12
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0a0+17540c5
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #safetensors #longt5 #text2text-generation #generated_from_trainer #summarization #base_model-google/long-t5-tglobal-base #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 12
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 3.0### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0a0+17540c5
* Datasets 2.3.2
* Tokenizers 0.12.1