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# t5-base-finetuned-resumes_t2json_large

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the resumes_t2json_large dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 4.3177
- Rouge2: 1.1704
- Rougel: 3.5786
- Rougelsum: 3.7496
- Gen Len: 18.4438

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.0           | 1.0   | 10280  | nan             | 4.3177 | 1.1704 | 3.5786 | 3.7496    | 18.4438 |
| 0.0           | 2.0   | 20560  | nan             | 4.3177 | 1.1704 | 3.5786 | 3.7496    | 18.4438 |
| 0.0           | 3.0   | 30840  | nan             | 4.3177 | 1.1704 | 3.5786 | 3.7496    | 18.4438 |
| 0.0           | 4.0   | 41120  | nan             | 4.3177 | 1.1704 | 3.5786 | 3.7496    | 18.4438 |
| 0.0           | 5.0   | 51400  | nan             | 4.3177 | 1.1704 | 3.5786 | 3.7496    | 18.4438 |
| 0.0           | 6.0   | 61680  | nan             | 4.3177 | 1.1704 | 3.5786 | 3.7496    | 18.4438 |
| 0.0           | 7.0   | 71960  | nan             | 4.3177 | 1.1704 | 3.5786 | 3.7496    | 18.4438 |
| 0.0           | 8.0   | 82240  | nan             | 4.3177 | 1.1704 | 3.5786 | 3.7496    | 18.4438 |
| 0.0           | 9.0   | 92520  | nan             | 4.3177 | 1.1704 | 3.5786 | 3.7496    | 18.4438 |
| 0.0           | 10.0  | 102800 | nan             | 4.3177 | 1.1704 | 3.5786 | 3.7496    | 18.4438 |


### Framework versions

- Transformers 4.20.1
- Pytorch 2.0.0+cu117
- Datasets 2.9.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["resumes_t2json_large"], "metrics": ["rouge"], "model-index": [{"name": "t5-base-finetuned-resumes_t2json_large", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "resumes_t2json_large", "type": "resumes_t2json_large", "args": "default"}, "metrics": [{"type": "rouge", "value": 4.3177, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer dataset:resumes_t2json_large 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-resumes_t2json_large #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-base-finetuned-resumes\_t2json\_large
========================================


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


* Loss: nan
* Rouge1: 4.3177
* Rouge2: 1.1704
* Rougel: 3.5786
* Rougelsum: 3.7496
* Gen Len: 18.4438


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 4.20.1
* Pytorch 2.0.0+cu117
* Datasets 2.9.0
* 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 4.20.1
* Pytorch 2.0.0+cu117
* Datasets 2.9.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-resumes_t2json_large #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 4.20.1
* Pytorch 2.0.0+cu117
* Datasets 2.9.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-resumes_t2json_large #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 4.20.1
* Pytorch 2.0.0+cu117
* Datasets 2.9.0
* Tokenizers 0.12.1