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# arxiv-summarization-t5-small-2022-09-05

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the ccdv/arxiv-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2994
- Rouge1: 37.7982
- Rouge2: 12.5571
- Rougel: 24.9325
- Rougelsum: 32.9189
- Gen Len: 122.0061

## 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: 3.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.5925        | 0.39  | 10000 | 2.4566          | 17.8432 | 6.6779 | 14.2303 | 16.1952   | 19.0    |
| 2.518         | 0.79  | 20000 | 2.3868          | 18.0354 | 6.8565 | 14.3552 | 16.3664   | 19.0    |
| 2.4587        | 1.18  | 30000 | 2.3600          | 18.2076 | 6.9618 | 14.5349 | 16.5626   | 19.0    |
| 2.4365        | 1.58  | 40000 | 2.3295          | 18.3579 | 7.0312 | 14.6145 | 16.6845   | 19.0    |
| 2.4306        | 1.97  | 50000 | 2.3190          | 18.4551 | 7.0861 | 14.6879 | 16.7627   | 19.0    |
| 2.4005        | 2.37  | 60000 | 2.3056          | 18.3521 | 7.0496 | 14.6413 | 16.6832   | 19.0    |
| 2.396         | 2.76  | 70000 | 2.3012          | 18.348  | 7.0439 | 14.6509 | 16.6994   | 19.0    |


### Framework versions

- Transformers 4.22.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["ccdv/arxiv-summarization"], "metrics": ["rouge"], "model-index": [{"name": "arxiv-summarization-t5-small-2022-09-05", "results": [{"task": {"type": "summarization", "name": "Summarization"}, "dataset": {"name": "ccdv/arxiv-summarization", "type": "ccdv/arxiv-summarization", "config": "section", "split": "train", "args": "section"}, "metrics": [{"type": "rouge", "value": 37.7982, "name": "Rouge1"}]}]}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:ccdv/arxiv-summarization license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-ccdv/arxiv-summarization #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

arxiv-summarization-t5-small-2022-09-05
=======================================


This model is a fine-tuned version of t5-small on the ccdv/arxiv-summarization dataset.
It achieves the following results on the evaluation set:


* Loss: 2.2994
* Rouge1: 37.7982
* Rouge2: 12.5571
* Rougel: 24.9325
* Rougelsum: 32.9189
* Gen Len: 122.0061


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: 3.0


### Training results



### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1



### 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: 3.0 ### Training results ### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-ccdv/arxiv-summarization #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: 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: 3.0 ### Training results ### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-ccdv/arxiv-summarization #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: 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: 3.0### Training results### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1