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# t5-small-finetuned-xsum

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2847
- Rouge1: 0.1422
- Rouge2: 0.0403
- Rougel: 0.1337
- Rougelsum: 0.1342
- Gen Len: 8.4248

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.7269        | 1.0   | 527  | 1.5826          | 0.0    | 0.0    | 0.0    | 0.0       | 0.0     |
| 1.5708        | 2.0   | 1054 | 1.4112          | 0.035  | 0.0105 | 0.0357 | 0.0349    | 1.7168  |
| 1.4796        | 3.0   | 1581 | 1.3644          | 0.1012 | 0.0167 | 0.0948 | 0.0942    | 8.2212  |
| 1.3451        | 4.0   | 2108 | 1.3399          | 0.126  | 0.0205 | 0.1183 | 0.1182    | 9.0088  |
| 1.3491        | 5.0   | 2635 | 1.3247          | 0.1307 | 0.0266 | 0.1232 | 0.1236    | 8.0088  |
| 1.3109        | 6.0   | 3162 | 1.3112          | 0.1428 | 0.0325 | 0.1332 | 0.1334    | 7.6549  |
| 1.2462        | 7.0   | 3689 | 1.3046          | 0.1435 | 0.0319 | 0.1342 | 0.1349    | 7.885   |
| 1.2353        | 8.0   | 4216 | 1.2937          | 0.1404 | 0.0313 | 0.1297 | 0.1303    | 9.1239  |
| 1.2838        | 9.0   | 4743 | 1.2903          | 0.1434 | 0.0372 | 0.1338 | 0.1344    | 8.1062  |
| 1.2317        | 10.0  | 5270 | 1.2870          | 0.1459 | 0.0421 | 0.1388 | 0.1389    | 8.4248  |
| 1.2598        | 11.0  | 5797 | 1.2857          | 0.1421 | 0.0403 | 0.1346 | 0.1351    | 8.2389  |
| 1.1579        | 12.0  | 6324 | 1.2847          | 0.1422 | 0.0403 | 0.1337 | 0.1342    | 8.4248  |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "pipeline_tag": "summarization", "model-index": [{"name": "t5-small-SA", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer summarization license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #summarization #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

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


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


* Loss: 1.2847
* Rouge1: 0.1422
* Rouge2: 0.0403
* Rougel: 0.1337
* Rougelsum: 0.1342
* Gen Len: 8.4248


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


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


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


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #summarization #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: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 12 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #summarization #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: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 12### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2