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# t5-small-finetuned-t5

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7570
- Rouge1: 70.2787
- Rouge2: 55.5377
- Rougel: 63.9121
- Rougelsum: 64.3555
- Gen Len: 17.2031

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 12   | 0.9687          | 65.8469 | 50.6135 | 60.4571 | 60.6727   | 16.8281 |
| No log        | 2.0   | 24   | 0.9260          | 65.8803 | 50.712  | 60.4633 | 60.6409   | 16.8125 |
| No log        | 3.0   | 36   | 0.8922          | 66.4957 | 50.843  | 60.8577 | 61.1762   | 17.0156 |
| No log        | 4.0   | 48   | 0.8663          | 67.4976 | 52.3429 | 61.5901 | 61.8548   | 16.8906 |
| No log        | 5.0   | 60   | 0.8471          | 67.7331 | 52.4301 | 61.4319 | 61.6517   | 16.9062 |
| No log        | 6.0   | 72   | 0.8304          | 68.0701 | 52.916  | 61.8953 | 62.0532   | 16.7812 |
| No log        | 7.0   | 84   | 0.8151          | 68.5051 | 53.9372 | 62.9052 | 63.0314   | 16.7969 |
| No log        | 8.0   | 96   | 0.8033          | 68.7841 | 54.2968 | 63.019  | 63.1808   | 16.9375 |
| No log        | 9.0   | 108  | 0.7928          | 68.9694 | 54.605  | 63.1564 | 63.4155   | 16.9844 |
| No log        | 10.0  | 120  | 0.7851          | 69.2494 | 54.8377 | 63.4448 | 63.7369   | 17.0312 |
| No log        | 11.0  | 132  | 0.7802          | 69.2075 | 54.9086 | 63.6303 | 63.8855   | 17.0312 |
| No log        | 12.0  | 144  | 0.7756          | 69.2319 | 54.8675 | 63.4849 | 63.928    | 17.0312 |
| No log        | 13.0  | 156  | 0.7716          | 69.0732 | 54.472  | 63.0335 | 63.4969   | 17.1562 |
| No log        | 14.0  | 168  | 0.7657          | 68.993  | 54.5342 | 62.9104 | 63.2738   | 17.0312 |
| No log        | 15.0  | 180  | 0.7632          | 70.1458 | 55.4883 | 63.8544 | 64.3299   | 17.2031 |
| No log        | 16.0  | 192  | 0.7614          | 69.8971 | 54.8277 | 63.4274 | 63.842    | 17.2031 |
| No log        | 17.0  | 204  | 0.7595          | 70.2733 | 55.4028 | 63.8387 | 64.2672   | 17.2031 |
| No log        | 18.0  | 216  | 0.7581          | 70.2787 | 55.5377 | 63.9121 | 64.3555   | 17.2031 |
| No log        | 19.0  | 228  | 0.7573          | 70.2787 | 55.5377 | 63.9121 | 64.3555   | 17.2031 |
| No log        | 20.0  | 240  | 0.7570          | 70.2787 | 55.5377 | 63.9121 | 64.3555   | 17.2031 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "t5-small-finetuned-t5", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

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


This model is a fine-tuned version of t5-small on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.7570
* Rouge1: 70.2787
* Rouge2: 55.5377
* Rougel: 63.9121
* Rougelsum: 64.3555
* Gen Len: 17.2031


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: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #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: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #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: 20
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3