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# bart-large-mnli-aitools-11n

This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1504
- Accuracy: 0.9631

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.05  | 50   | 0.5899          | 0.9171   |
| No log        | 0.1   | 100  | 0.2924          | 0.9171   |
| No log        | 0.15  | 150  | 0.1300          | 0.9171   |
| No log        | 0.21  | 200  | 0.3631          | 0.9447   |
| No log        | 0.26  | 250  | 0.1954          | 0.9493   |
| No log        | 0.31  | 300  | 0.2654          | 0.9447   |
| No log        | 0.36  | 350  | 0.3464          | 0.9401   |
| No log        | 0.41  | 400  | 0.1400          | 0.9585   |
| No log        | 0.46  | 450  | 0.1686          | 0.9631   |
| 0.311         | 0.51  | 500  | 0.2399          | 0.9447   |
| 0.311         | 0.56  | 550  | 0.2273          | 0.9585   |
| 0.311         | 0.62  | 600  | 0.0956          | 0.9770   |
| 0.311         | 0.67  | 650  | 0.1788          | 0.9309   |
| 0.311         | 0.72  | 700  | 0.1840          | 0.9447   |
| 0.311         | 0.77  | 750  | 0.1828          | 0.9631   |
| 0.311         | 0.82  | 800  | 0.0765          | 0.9770   |
| 0.311         | 0.87  | 850  | 0.1851          | 0.9585   |
| 0.311         | 0.92  | 900  | 0.0854          | 0.9724   |
| 0.311         | 0.97  | 950  | 0.0783          | 0.9724   |
| 0.2123        | 1.03  | 1000 | 0.1504          | 0.9631   |
| 0.2123        | 1.08  | 1050 | 0.2845          | 0.9585   |
| 0.2123        | 1.13  | 1100 | 0.2655          | 0.9585   |
| 0.2123        | 1.18  | 1150 | 0.1718          | 0.9585   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "bart-large-mnli-aitools-11n", "results": []}]}
transformers pytorch tensorboard bart text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

bart-large-mnli-aitools-11n
===========================


This model is a fine-tuned version of facebook/bart-large-mnli on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1504
* Accuracy: 0.9631


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: 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: 5


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 5 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bart #text-classification #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: 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: 5 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bart #text-classification #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: 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: 5### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2