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# pegasus-newsroom-cnn-adam8bit-bs4x64acc

This model is a fine-tuned version of [oMateos2020/pegasus-newsroom-cnn-adam8bit-bs16x64acc](https://huggingface.co/oMateos2020/pegasus-newsroom-cnn-adam8bit-bs16x64acc) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8608
- Rouge1: 44.2881
- Rouge2: 21.5487
- Rougel: 31.3798
- Rougelsum: 41.2326
- Gen Len: 71.7744

## 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: 6.4e-05
- train_batch_size: 4
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.4
- num_epochs: 1
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.9307        | 1.0   | 1121 | 2.8608          | 44.2881 | 21.5487 | 31.3798 | 41.2326   | 71.7744 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "datasets": ["cnn_dailymail"], "metrics": ["rouge"], "model-index": [{"name": "pegasus-newsroom-cnn-adam8bit-bs4x64acc", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "cnn_dailymail", "type": "cnn_dailymail", "args": "3.0.0"}, "metrics": [{"type": "rouge", "value": 44.2881, "name": "Rouge1"}]}]}]}
transformers pytorch pegasus text2text-generation generated_from_trainer dataset:cnn_dailymail model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #pegasus #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #model-index #autotrain_compatible #endpoints_compatible #region-us 

pegasus-newsroom-cnn-adam8bit-bs4x64acc
=======================================


This model is a fine-tuned version of oMateos2020/pegasus-newsroom-cnn-adam8bit-bs16x64acc on the cnn\_dailymail dataset.
It achieves the following results on the evaluation set:


* Loss: 2.8608
* Rouge1: 44.2881
* Rouge2: 21.5487
* Rougel: 31.3798
* Rougelsum: 41.2326
* Gen Len: 71.7744


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: 6.4e-05
* train\_batch\_size: 4
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 64
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.4
* num\_epochs: 1
* mixed\_precision\_training: Native AMP
* label\_smoothing\_factor: 0.1


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 6.4e-05
* train\_batch\_size: 4
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 64
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.4
* num\_epochs: 1
* mixed\_precision\_training: Native AMP
* label\_smoothing\_factor: 0.1 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #pegasus #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 6.4e-05
* train\_batch\_size: 4
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 64
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.4
* num\_epochs: 1
* mixed\_precision\_training: Native AMP
* label\_smoothing\_factor: 0.1 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #pegasus #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 6.4e-05
* train\_batch\_size: 4
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 64
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.4
* num\_epochs: 1
* mixed\_precision\_training: Native AMP
* label\_smoothing\_factor: 0.1### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1