
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bart-cnn-pubmed-arxiv-pubmed-v3-e43

This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv-pubmed](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv-pubmed) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0837
- Rouge1: 58.1526
- Rouge2: 46.0425
- Rougel: 49.5624
- Rougelsum: 56.9295
- 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: 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: 43
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 1.2542        | 1.0   | 795   | 0.9354          | 51.4655 | 31.6464 | 34.2376 | 48.9765   | 141.963  |
| 0.7019        | 2.0   | 1590  | 0.8119          | 53.3066 | 34.683  | 36.4262 | 50.907    | 142.0    |
| 0.5251        | 3.0   | 2385  | 0.7839          | 52.4248 | 32.8685 | 36.0084 | 49.9957   | 142.0    |
| 0.3449        | 4.0   | 3180  | 0.7673          | 52.716  | 34.7869 | 38.4201 | 50.8384   | 142.0    |
| 0.2666        | 5.0   | 3975  | 0.7647          | 54.6433 | 37.1337 | 40.1459 | 52.4288   | 141.7778 |
| 0.1805        | 6.0   | 4770  | 0.8400          | 53.5747 | 36.001  | 39.5984 | 51.1935   | 141.8148 |
| 0.1413        | 7.0   | 5565  | 0.7925          | 53.9875 | 37.01   | 40.6532 | 51.9353   | 142.0    |
| 0.113         | 8.0   | 6360  | 0.7665          | 56.395  | 41.5764 | 44.327  | 54.7845   | 142.0    |
| 0.0907        | 9.0   | 7155  | 0.8442          | 55.1407 | 39.4113 | 43.0628 | 53.6503   | 142.0    |
| 0.0824        | 10.0  | 7950  | 0.8469          | 55.7103 | 40.6761 | 43.3754 | 53.8227   | 142.0    |
| 0.0639        | 11.0  | 8745  | 0.8892          | 56.0839 | 40.6204 | 43.2455 | 54.4412   | 142.0    |
| 0.0504        | 12.0  | 9540  | 0.8613          | 56.9634 | 42.8236 | 45.4255 | 55.4026   | 142.0    |
| 0.0447        | 13.0  | 10335 | 0.9341          | 57.7216 | 44.104  | 47.1429 | 56.4299   | 142.0    |
| 0.0396        | 14.0  | 11130 | 0.9203          | 56.2073 | 42.9575 | 45.8068 | 54.8089   | 142.0    |
| 0.036         | 15.0  | 11925 | 0.9253          | 58.5212 | 45.6047 | 49.1205 | 57.0551   | 142.0    |
| 0.0302        | 16.0  | 12720 | 0.9187          | 58.8046 | 46.0106 | 48.0442 | 57.2799   | 142.0    |
| 0.0261        | 17.0  | 13515 | 0.9578          | 57.3405 | 43.8227 | 46.6317 | 55.7836   | 142.0    |
| 0.0231        | 18.0  | 14310 | 0.9578          | 57.7604 | 44.6164 | 47.8902 | 56.2309   | 141.8148 |
| 0.0198        | 19.0  | 15105 | 0.9662          | 57.774  | 44.6407 | 47.5489 | 56.1936   | 142.0    |
| 0.0165        | 20.0  | 15900 | 0.9509          | 59.6297 | 46.5076 | 48.3507 | 58.083    | 142.0    |
| 0.0145        | 21.0  | 16695 | 0.9915          | 58.2245 | 45.1804 | 48.1191 | 56.889    | 142.0    |
| 0.0128        | 22.0  | 17490 | 0.9945          | 58.2646 | 46.2782 | 49.4411 | 56.992    | 142.0    |
| 0.0129        | 23.0  | 18285 | 1.0069          | 57.0055 | 44.1866 | 46.9101 | 55.5056   | 141.9444 |
| 0.0116        | 24.0  | 19080 | 0.9967          | 58.1091 | 45.5303 | 48.2208 | 56.4496   | 142.0    |
| 0.0093        | 25.0  | 19875 | 1.0188          | 56.59   | 43.677  | 45.8956 | 55.0954   | 142.0    |
| 0.008         | 26.0  | 20670 | 0.9976          | 58.5408 | 46.7019 | 48.9235 | 57.2562   | 142.0    |
| 0.0077        | 27.0  | 21465 | 1.0123          | 57.7909 | 45.7619 | 48.3412 | 56.3796   | 142.0    |
| 0.0075        | 28.0  | 22260 | 1.0258          | 58.1694 | 45.03   | 48.282  | 56.7303   | 142.0    |
| 0.0056        | 29.0  | 23055 | 1.0100          | 58.0406 | 45.37   | 48.0125 | 56.5288   | 142.0    |
| 0.0049        | 30.0  | 23850 | 1.0235          | 56.419  | 43.248  | 46.3448 | 54.8467   | 142.0    |
| 0.0042        | 31.0  | 24645 | 1.0395          | 57.7232 | 45.6305 | 48.4531 | 56.3343   | 141.9444 |
| 0.0034        | 32.0  | 25440 | 1.0605          | 58.9049 | 46.8049 | 49.9103 | 57.6751   | 141.5    |
| 0.0032        | 33.0  | 26235 | 1.0362          | 57.8681 | 45.9028 | 48.8624 | 56.5616   | 141.8704 |
| 0.0025        | 34.0  | 27030 | 1.0521          | 58.8985 | 46.8547 | 49.8485 | 57.4249   | 142.0    |
| 0.0021        | 35.0  | 27825 | 1.0639          | 58.9324 | 46.656  | 49.1907 | 57.4836   | 142.0    |
| 0.0023        | 36.0  | 28620 | 1.0624          | 58.5734 | 46.6774 | 49.6377 | 57.3825   | 142.0    |
| 0.0019        | 37.0  | 29415 | 1.0636          | 58.9899 | 46.8217 | 49.4829 | 57.8683   | 142.0    |
| 0.0018        | 38.0  | 30210 | 1.0640          | 58.793  | 46.7964 | 49.7845 | 57.6379   | 142.0    |
| 0.0013        | 39.0  | 31005 | 1.0692          | 57.7124 | 45.5948 | 49.0482 | 56.4246   | 142.0    |
| 0.0012        | 40.0  | 31800 | 1.0746          | 58.1789 | 46.458  | 49.547  | 57.1007   | 141.6296 |
| 0.0008        | 41.0  | 32595 | 1.0815          | 57.7392 | 45.6404 | 48.4845 | 56.6464   | 142.0    |
| 0.0009        | 42.0  | 33390 | 1.0853          | 58.317  | 46.2661 | 49.0466 | 57.0971   | 142.0    |
| 0.0005        | 43.0  | 34185 | 1.0837          | 58.1526 | 46.0425 | 49.5624 | 56.9295   | 142.0    |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "bart-cnn-pubmed-arxiv-pubmed-v3-e43", "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-v3-e43
===================================


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


* Loss: 1.0837
* Rouge1: 58.1526
* Rouge2: 46.0425
* Rougel: 49.5624
* Rougelsum: 56.9295
* 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: 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: 43
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 43
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* 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: 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: 43
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* 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: 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: 43
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1