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# bart-cnn-pubmed-arxiv-pubmed-arxiv-earlystopping

This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8793
- Rouge1: 56.2055
- Rouge2: 41.9231
- Rougel: 45.0616
- Rougelsum: 54.6643
- Gen Len: 142.0

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| No log        | 0.31  | 125  | 1.2057          | 50.9339 | 30.6777 | 32.6396 | 47.9592   | 141.3519 |
| No log        | 0.63  | 250  | 1.0933          | 52.0728 | 31.2361 | 32.8214 | 48.9776   | 141.9815 |
| No log        | 0.94  | 375  | 0.9685          | 51.6847 | 32.1578 | 34.1933 | 48.8808   | 141.5556 |
| 1.1594        | 1.26  | 500  | 0.9725          | 50.5131 | 30.6043 | 32.1861 | 47.4346   | 142.0    |
| 1.1594        | 1.57  | 625  | 0.9342          | 52.228  | 32.2073 | 33.797  | 49.2395   | 142.0    |
| 1.1594        | 1.88  | 750  | 0.8715          | 52.2    | 33.6602 | 36.1303 | 49.7138   | 141.6481 |
| 1.1594        | 2.2   | 875  | 0.8334          | 53.116  | 33.9871 | 35.9641 | 50.7658   | 141.8889 |
| 0.6845        | 2.51  | 1000 | 0.8241          | 52.2612 | 32.8025 | 35.27   | 49.5694   | 142.0    |
| 0.6845        | 2.83  | 1125 | 0.7986          | 54.1803 | 35.0019 | 37.4582 | 51.4577   | 142.0    |
| 0.6845        | 3.14  | 1250 | 0.8532          | 52.1328 | 32.6086 | 34.7455 | 49.6219   | 141.7037 |
| 0.6845        | 3.45  | 1375 | 0.8319          | 51.9614 | 32.8544 | 35.3269 | 49.3279   | 141.7593 |
| 0.4488        | 3.77  | 1500 | 0.8033          | 53.1404 | 34.6086 | 37.5482 | 50.7414   | 142.0    |
| 0.4488        | 4.08  | 1625 | 0.8322          | 53.1736 | 34.8662 | 37.7514 | 51.0601   | 142.0    |
| 0.4488        | 4.4   | 1750 | 0.7985          | 51.8251 | 32.9457 | 36.4164 | 49.55     | 142.0    |
| 0.4488        | 4.71  | 1875 | 0.8049          | 54.3423 | 36.6293 | 39.1316 | 52.2706   | 141.8148 |
| 0.3017        | 5.03  | 2000 | 0.8148          | 53.0698 | 35.2569 | 38.406  | 50.9346   | 141.7778 |
| 0.3017        | 5.34  | 2125 | 0.8153          | 53.4479 | 35.1525 | 37.8071 | 51.3731   | 141.0741 |
| 0.3017        | 5.65  | 2250 | 0.8009          | 52.5517 | 34.8287 | 37.999  | 50.2889   | 141.6111 |
| 0.3017        | 5.97  | 2375 | 0.7509          | 54.2725 | 37.4164 | 40.516  | 52.1379   | 142.0    |
| 0.2052        | 6.28  | 2500 | 0.8019          | 54.622  | 36.4776 | 39.9306 | 52.5069   | 142.0    |
| 0.2052        | 6.6   | 2625 | 0.8176          | 55.4796 | 38.4502 | 41.5523 | 53.5211   | 142.0    |
| 0.2052        | 6.91  | 2750 | 0.7956          | 55.4906 | 37.9064 | 40.845  | 53.107    | 141.9815 |
| 0.2052        | 7.22  | 2875 | 0.7966          | 54.5177 | 37.3399 | 40.7678 | 52.4241   | 142.0    |
| 0.1465        | 7.54  | 3000 | 0.8311          | 54.3473 | 37.0659 | 40.2507 | 52.372    | 142.0    |
| 0.1465        | 7.85  | 3125 | 0.8227          | 53.9245 | 36.4695 | 39.1205 | 51.9416   | 141.8889 |
| 0.1465        | 8.17  | 3250 | 0.7947          | 54.766  | 38.4275 | 41.2293 | 52.9075   | 142.0    |
| 0.1465        | 8.48  | 3375 | 0.7954          | 54.5305 | 37.6934 | 40.6804 | 52.5884   | 141.9444 |
| 0.115         | 8.79  | 3500 | 0.8433          | 54.7962 | 37.9373 | 41.3906 | 52.3778   | 142.0    |
| 0.115         | 9.11  | 3625 | 0.8416          | 56.59   | 41.2271 | 44.4207 | 54.7199   | 142.0    |
| 0.115         | 9.42  | 3750 | 0.8164          | 55.1903 | 39.0588 | 41.4908 | 53.4897   | 142.0    |
| 0.115         | 9.74  | 3875 | 0.8363          | 55.2894 | 39.3598 | 42.1138 | 53.831    | 141.8889 |
| 0.0912        | 10.05 | 4000 | 0.8850          | 55.7705 | 40.4924 | 43.1048 | 54.254    | 142.0    |
| 0.0912        | 10.36 | 4125 | 0.8268          | 56.1664 | 40.641  | 42.798  | 54.0001   | 141.9259 |
| 0.0912        | 10.68 | 4250 | 0.8564          | 55.4701 | 39.4949 | 42.2559 | 53.4486   | 141.8889 |
| 0.0912        | 10.99 | 4375 | 0.8557          | 56.0849 | 41.2861 | 45.8277 | 54.5999   | 141.6667 |
| 0.0707        | 11.31 | 4500 | 0.8432          | 54.9496 | 39.3006 | 42.0025 | 53.3854   | 142.0    |
| 0.0707        | 11.62 | 4625 | 0.8377          | 54.2438 | 37.6959 | 40.4637 | 52.3088   | 142.0    |
| 0.0707        | 11.93 | 4750 | 0.8794          | 55.9488 | 40.5401 | 43.7347 | 54.1282   | 142.0    |
| 0.0707        | 12.25 | 4875 | 0.8563          | 57.8762 | 43.366  | 46.6757 | 56.6985   | 142.0    |
| 0.0604        | 12.56 | 5000 | 0.8835          | 54.8926 | 39.3755 | 42.384  | 53.2687   | 141.6481 |
| 0.0604        | 12.88 | 5125 | 0.8570          | 55.6656 | 39.849  | 42.1455 | 54.352    | 142.0    |
| 0.0604        | 13.19 | 5250 | 0.8539          | 57.1549 | 41.901  | 45.153  | 55.213    | 142.0    |
| 0.0604        | 13.51 | 5375 | 0.8847          | 56.3279 | 40.9269 | 43.416  | 54.7242   | 142.0    |
| 0.051         | 13.82 | 5500 | 0.8795          | 56.8982 | 42.3333 | 45.2669 | 55.1034   | 142.0    |
| 0.051         | 14.13 | 5625 | 0.8751          | 55.3173 | 40.2853 | 43.2479 | 53.7236   | 142.0    |
| 0.051         | 14.45 | 5750 | 0.8799          | 56.1678 | 41.0862 | 43.8581 | 54.6316   | 142.0    |
| 0.051         | 14.76 | 5875 | 0.8678          | 57.3539 | 43.0473 | 44.8511 | 55.6474   | 142.0    |
| 0.0467        | 15.08 | 6000 | 0.8945          | 56.1939 | 41.985  | 45.0266 | 54.8139   | 142.0    |
| 0.0467        | 15.39 | 6125 | 0.9245          | 56.2071 | 41.5265 | 44.3228 | 54.5042   | 141.4074 |
| 0.0467        | 15.7  | 6250 | 0.8793          | 56.2055 | 41.9231 | 45.0616 | 54.6643   | 142.0    |


### Framework versions

- Transformers 4.19.1
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "bart-cnn-pubmed-arxiv-pubmed-arxiv-earlystopping", "results": []}]}
transformers pytorch tensorboard bart text2text-generation generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

bart-cnn-pubmed-arxiv-pubmed-arxiv-earlystopping
================================================


This model is a fine-tuned version of theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.8793
* Rouge1: 56.2055
* Rouge2: 41.9231
* Rougel: 45.0616
* Rougelsum: 54.6643
* Gen Len: 142.0


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: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.19.1
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.1
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.1
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.19.1
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1