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# t5-base-finetuned-xsum

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the resumes_t2json dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5861
- Rouge1: 5.7966
- Rouge2: 3.5884
- Rougel: 5.7799
- Rougelsum: 5.7839
- Gen Len: 19.0

## 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.2507        | 1.0   | 877  | 0.5862          | 5.7975 | 3.5884 | 5.7804 | 5.7847    | 19.0    |
| 0.7138        | 2.0   | 1754 | 0.5861          | 5.7966 | 3.5884 | 5.7799 | 5.7839    | 19.0    |
| 0.7176        | 3.0   | 2631 | 0.5861          | 5.7966 | 3.5884 | 5.7799 | 5.7839    | 19.0    |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["resumes_t2json"], "metrics": ["rouge"], "model-index": [{"name": "t5-base-finetuned-xsum", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "resumes_t2json", "type": "resumes_t2json", "config": "default", "split": "validation", "args": "default"}, "metrics": [{"type": "rouge", "value": 5.7966, "name": "Rouge1"}]}]}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:resumes_t2json license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-resumes_t2json #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-base-finetuned-xsum
======================


This model is a fine-tuned version of t5-base on the resumes\_t2json dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5861
* Rouge1: 5.7966
* Rouge2: 3.5884
* Rougel: 5.7799
* Rougelsum: 5.7839
* Gen Len: 19.0


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: 3
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2



### 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: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-resumes_t2json #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: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-resumes_t2json #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: 3
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.9.0
* Tokenizers 0.13.2