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# bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-multi-news

This model is a fine-tuned version of [mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization](https://huggingface.co/mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0185
- Rouge1: 38.9616
- Rouge2: 14.1539
- Rougel: 21.1788
- Rougelsum: 35.314

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 3.3679        | 1.0   | 11243 | 3.1314          | 38.4459 | 13.7777 | 20.8772 | 34.8321   |
| 3.1115        | 2.0   | 22486 | 3.0589          | 38.7419 | 13.9355 | 20.9911 | 35.0988   |
| 2.9826        | 3.0   | 33729 | 3.0311          | 38.7345 | 14.0365 | 21.0571 | 35.1604   |
| 2.8986        | 4.0   | 44972 | 3.0185          | 38.9616 | 14.1539 | 21.1788 | 35.314    |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["summarisation", "generated_from_trainer"], "datasets": ["multi_news"], "metrics": ["rouge"], "model-index": [{"name": "bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-multi-news", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "multi_news", "type": "multi_news", "args": "default"}, "metrics": [{"type": "rouge", "value": 38.9616, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard encoder-decoder text2text-generation summarisation generated_from_trainer dataset:multi_news license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #encoder-decoder #text2text-generation #summarisation #generated_from_trainer #dataset-multi_news #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-small2bert-small-finetuned-cnn\_daily\_mail-summarization-finetuned-multi-news
===================================================================================


This model is a fine-tuned version of mrm8488/bert-small2bert-small-finetuned-cnn\_daily\_mail-summarization on the multi\_news dataset.
It achieves the following results on the evaluation set:


* Loss: 3.0185
* Rouge1: 38.9616
* Rouge2: 14.1539
* Rougel: 21.1788
* Rougelsum: 35.314


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: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #encoder-decoder #text2text-generation #summarisation #generated_from_trainer #dataset-multi_news #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #encoder-decoder #text2text-generation #summarisation #generated_from_trainer #dataset-multi_news #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1