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# flan-t5-base-xsum

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0798
- Rouge1: 32.3503
- Rouge2: 10.8909
- Rougel: 25.9346
- Rougelsum: 25.9216
- Gen Len: 18.8494

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.335         | 1.0   | 1417 | 2.0823          | 31.3453 | 10.2077 | 25.0051 | 25.008    | 18.8259 |
| 1.8642        | 2.0   | 2834 | 2.0798          | 32.3503 | 10.8909 | 25.9346 | 25.9216   | 18.8494 |
| 1.5208        | 3.0   | 4251 | 2.1272          | 32.6743 | 11.3394 | 26.3776 | 26.3724   | 18.8435 |
| 1.2628        | 4.0   | 5668 | 2.2110          | 32.695  | 11.3273 | 26.3215 | 26.322    | 18.8306 |
| 1.0649        | 5.0   | 7085 | 2.3143          | 32.5287 | 11.3662 | 26.274  | 26.2741   | 18.8345 |


### 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"], "datasets": ["xsum"], "metrics": ["rouge"], "base_model": "google/flan-t5-base", "model-index": [{"name": "flan-t5-base-xsum", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "xsum", "type": "xsum", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "rouge", "value": 32.3503, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer dataset:xsum base_model:google/flan-t5-base 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-xsum #base_model-google/flan-t5-base #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

flan-t5-base-xsum
=================


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


* Loss: 2.0798
* Rouge1: 32.3503
* Rouge2: 10.8909
* Rougel: 25.9346
* Rougelsum: 25.9216
* Gen Len: 18.8494


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: 0.0005
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adafactor
* lr\_scheduler\_type: linear
* num\_epochs: 5


### 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: 0.0005
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adafactor
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### 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 #dataset-xsum #base_model-google/flan-t5-base #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: 0.0005
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adafactor
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### 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 #dataset-xsum #base_model-google/flan-t5-base #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: 0.0005
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adafactor
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


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