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# first_tldr

This model is a fine-tuned version of [pszemraj/long-t5-tglobal-base-16384-book-summary](https://huggingface.co/pszemraj/long-t5-tglobal-base-16384-book-summary) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4427
- Rouge1: 0.3859
- Rouge2: 0.1307
- Rougel: 0.2443

## 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: 0.0005
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 128
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| No log        | 0.98  | 47   | 1.4361          | 0.3848 | 0.1323 | 0.2419 |
| No log        | 1.97  | 94   | 1.4427          | 0.3859 | 0.1307 | 0.2443 |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "bsd-3-clause", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "first_tldr", "results": []}]}
transformers pytorch tensorboard longt5 text2text-generation generated_from_trainer license:bsd-3-clause autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #longt5 #text2text-generation #generated_from_trainer #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #region-us 

first\_tldr
===========


This model is a fine-tuned version of pszemraj/long-t5-tglobal-base-16384-book-summary on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.4427
* Rouge1: 0.3859
* Rouge2: 0.1307
* Rougel: 0.2443


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: 0.0005
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 128
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* num\_epochs: 2


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 1.12.1+cu116
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 128
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* num\_epochs: 2 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 1.12.1+cu116
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #longt5 #text2text-generation #generated_from_trainer #license-bsd-3-clause #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 128
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* num\_epochs: 2 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 1.12.1+cu116
* Datasets 2.4.0
* Tokenizers 0.12.1