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# t5-small-booksum-finetuned-booksum-test

This model is a fine-tuned version of [cnicu/t5-small-booksum](https://huggingface.co/cnicu/t5-small-booksum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2739
- Rouge1: 22.7829
- Rouge2: 4.8349
- Rougel: 18.2465
- Rougelsum: 19.2417

## 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: 5.6e-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: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.5123        | 1.0   | 8750  | 3.2816          | 21.7712 | 4.3046 | 17.4053 | 18.4707   |
| 3.2347        | 2.0   | 17500 | 3.2915          | 22.2938 | 4.7828 | 17.8567 | 18.9135   |
| 3.0892        | 3.0   | 26250 | 3.2568          | 22.4966 | 4.825  | 18.0344 | 19.1306   |
| 2.9837        | 4.0   | 35000 | 3.2952          | 22.6913 | 5.0322 | 18.176  | 19.2751   |
| 2.9028        | 5.0   | 43750 | 3.2626          | 22.3548 | 4.7521 | 17.8681 | 18.7815   |
| 2.8441        | 6.0   | 52500 | 3.2691          | 22.6279 | 4.932  | 18.1051 | 19.0763   |
| 2.8006        | 7.0   | 61250 | 3.2753          | 22.8911 | 4.8954 | 18.1204 | 19.1464   |
| 2.7742        | 8.0   | 70000 | 3.2739          | 22.7829 | 4.8349 | 18.2465 | 19.2417   |


### Framework versions

- Transformers 4.19.1
- Pytorch 1.7.0
- Datasets 2.2.1
- Tokenizers 0.12.1

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

t5-small-booksum-finetuned-booksum-test
=======================================


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


* Loss: 3.2739
* Rouge1: 22.7829
* Rouge2: 4.8349
* Rougel: 18.2465
* Rougelsum: 19.2417


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: 5.6e-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: 8


### Training results



### Framework versions


* Transformers 4.19.1
* Pytorch 1.7.0
* Datasets 2.2.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-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: 8 ### Training results ### Framework versions


* Transformers 4.19.1
* Pytorch 1.7.0
* Datasets 2.2.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #summarization #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-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: 8 ### Training results ### Framework versions


* Transformers 4.19.1
* Pytorch 1.7.0
* Datasets 2.2.1
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #summarization #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-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: 8### Training results### Framework versions


* Transformers 4.19.1
* Pytorch 1.7.0
* Datasets 2.2.1
* Tokenizers 0.12.1