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# flan-t5-base-samsum

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3709
- Rouge1: 46.8876
- Rouge2: 23.2689
- Rougel: 39.5369
- Rougelsum: 43.1602
- Gen Len: 17.2027

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4403        | 1.0   | 1842 | 1.3829          | 46.5321 | 23.0912 | 39.4008 | 42.8993   | 17.0977 |
| 1.3534        | 2.0   | 3684 | 1.3732          | 47.1111 | 23.4456 | 39.5462 | 43.2534   | 17.4554 |
| 1.2795        | 3.0   | 5526 | 1.3709          | 46.8876 | 23.2689 | 39.5369 | 43.1602   | 17.2027 |
| 1.2313        | 4.0   | 7368 | 1.3736          | 47.4418 | 23.701  | 39.9856 | 43.6294   | 17.2198 |
| 1.1934        | 5.0   | 9210 | 1.3772          | 47.4656 | 23.9199 | 40.0284 | 43.7039   | 17.3162 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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Olivia: That would be great!", "example_title": "Dialogue 1"}, {"text": "Chad: Elton John is goat Eva: what do you mean by goat? Frank: greatest of all time Chad: indeed Eva: ahh... it makes sense now :P", "example_title": "Dialogue 2"}, {"text": "Astonishing X-Men is the name of four X-Men comic book series from Marvel Comics, the first two of which were limited series. The third volume, an ongoing series, began in 2004, with its first run written by Joss Whedon and art by John Cassaday. It was then written by Warren Ellis with art by Simone Bianchi and Phil Jimenez.[1] Daniel Way and Christos Gage then took over the title writing alternating stories. They were followed by James Asmus who wrote one issue, then Greg Pak, who took over for four issues in November 2011.[2] Marjorie Liu wrote the final 21 issues of the series until its end at issue #68 in 2013. The title's fourth volume and second ongoing series launched in 2017 during the \"ResurrXion\" storyline.[3] The first run was written by Charles Soule and illustrated by a rotating cast of artists. Matthew Rosenberg and artist Greg Land would then take over the series before its end in 2018. The original Astonishing X-Men was a four-issue limited series that replaced Uncanny X-Men during the 1995 alternate universe storyline \"Age of Apocalypse\", in which all X-titles were given new names and issue numbers. In the storyline, Professor X was murdered 20 years in the past by his own son, Legion. Magneto, witnessing his friend's death, committed himself to Xavier's dream and created his own team of X-Men. However, he was unable to prevent the rise of the despotic Apocalypse and hence the series primarily dealt with the X-Men's battle against him. Astonishing X-Men, written by Scott Lobdell and illustrated by Joe Madureira, featured a team of X-Men led by Rogue and consisted of Sunfire, Blink, Morph, Sabretooth and Wildchild. source: https://en.wikipedia.org/wiki/Astonishing_X-Men", "example_title": "Wikipedia Article"}], "model-index": [{"name": "flan-t5-base-samsum", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "samsum", "type": "samsum", "config": "samsum", "split": "test", "args": "samsum"}, "metrics": [{"type": "rouge", "value": 46.8876, "name": "Rouge1"}]}, {"task": {"type": "summarization", "name": "Summarization"}, "dataset": {"name": "samsum", "type": "samsum", "config": "samsum", "split": "test"}, "metrics": [{"type": "rouge", "value": 47.1604, "name": "ROUGE-1", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzAzNjBhZmU3ZWE1Nzg2OGNmNWQxZTRkMWI3MGJmY2U3NzdiN2NhMzA2ZGY2N2VmOGQzNThkZDg5YmI1NTQzMCIsInZlcnNpb24iOjF9.fj5dvLTJmdTud-r9NBx468b_q7128WFc84Oa_ogUq1YuHfgK9KRBJl0V8YVP-UrVOB-5Mwcy_kVo2gqUq2fQCA"}, {"type": "rouge", "value": 23.5947, "name": "ROUGE-2", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2ExZTYyMDMzYjQyZWU0NjY4YWZiN2NjMjAyNzUwMzU3ZjQxOTdjZDdhNjE0MDE1NDVmY2Y5MDEyZTI5ODA5ZCIsInZlcnNpb24iOjF9.4XKnhKi4PtU0KnyXnBDRop-tWwDvAgJqbWkuPAVUPThcCjVrpjLiSgTWP49NEK-l3QBaLluoh7M-OF8OTwasBQ"}, {"type": "rouge", "value": 39.7299, "name": "ROUGE-L", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYWZiMDU1ODY4Y2ViOWJlZjhhZTAzNjY4NDhjYzdlYzg1MDRmZDM2ZDFkZGVhNjQzMmZjZDA3OWEzYjUzOTU0NCIsInZlcnNpb24iOjF9.EctQIDlK_ksR7NiCtHsxnWWzUF8WNmZ58JIsTUTjQPqmf8Igm82tihK78S4nit7IF24lug5_Ua7X5gWzMHDvDA"}, {"type": "rouge", "value": 43.3052, "name": "ROUGE-LSUM", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzQwYTMyOGNlNzJiNDEzMjQ5NzEwMzMyZmRhZDAxOGNhMWNkZjA0YWEyM2NkZGU3ODU3ZDU4ZWFhODkyNzNkOCIsInZlcnNpb24iOjF9.nsQAnUdVTySov7ZkNYJjMbIjb7V87D1w0HFLdOzSq5gaKuZmkAXmh14c_bL4Fbyf3AV_skLCDCJZEnsJHN7mDQ"}, {"type": "loss", "value": 1.3786224126815796, "name": "loss", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDgzMTkxY2EwOWU5MDgyODM3ZjE3MzBiN2Q0YmQ5MDI2MjI2NWNmMjUwZDY4MjZkZDg4ODcwMzVkN2Q4NTRmNSIsInZlcnNpb24iOjF9.vV700h6j3hdlzf-CEDIR3C9XND1jH3nW0r6Njgw0qB3Avfsq6zywr8ip2sxoo6aFCCQcmmcnmHiy7x1_xdwYAA"}, {"type": "gen_len", "value": 17.3443, "name": "gen_len", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTNjYjFiYjgzNjBlMDY2MWUwZTVmY2Y1OWMwNGZkZTg0Mzc5ZmU2MWIwOWZlYWMzZGM1YWI0NTJjOTFhOTU2YiIsInZlcnNpb24iOjF9.-RshHr8uVG0B4qGh5Tr3bgqqai9R_Xho0M9iQyd5g0fyQJlYhIT12cUkcy2_NKUJEqu_JxSul723UWpiZgBHAQ"}]}]}]}
transformers pytorch tensorboard safetensors t5 text2text-generation generated_from_trainer summarization en dataset:samsum license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #summarization #en #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

flan-t5-base-samsum
===================


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


* Loss: 1.3709
* Rouge1: 46.8876
* Rouge2: 23.2689
* Rougel: 39.5369
* Rougelsum: 43.1602
* Gen Len: 17.2027


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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #summarization #en #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #summarization #en #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2