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# bart-large-mnli-aitools-6n

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: 0.2748
- Accuracy: 0.9444

## 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        | 0.09  | 50   | 0.0885          | 0.9762   |
| No log        | 0.18  | 100  | 0.4805          | 0.8571   |
| No log        | 0.26  | 150  | 0.2582          | 0.9524   |
| No log        | 0.35  | 200  | 0.2742          | 0.9286   |
| No log        | 0.44  | 250  | 0.1553          | 0.9683   |
| No log        | 0.53  | 300  | 0.2574          | 0.9603   |
| No log        | 0.62  | 350  | 0.3690          | 0.9444   |
| No log        | 0.7   | 400  | 0.3113          | 0.9365   |
| No log        | 0.79  | 450  | 0.3474          | 0.9206   |
| 0.3671        | 0.88  | 500  | 0.2385          | 0.9206   |
| 0.3671        | 0.97  | 550  | 0.2947          | 0.9365   |
| 0.3671        | 1.05  | 600  | 0.2834          | 0.9444   |
| 0.3671        | 1.14  | 650  | 0.2425          | 0.9524   |
| 0.3671        | 1.23  | 700  | 0.2494          | 0.9524   |
| 0.3671        | 1.32  | 750  | 0.3040          | 0.9444   |
| 0.3671        | 1.41  | 800  | 0.2974          | 0.9444   |
| 0.3671        | 1.49  | 850  | 0.2268          | 0.9683   |
| 0.3671        | 1.58  | 900  | 0.3889          | 0.9365   |
| 0.3671        | 1.67  | 950  | 0.3333          | 0.8968   |
| 0.1777        | 1.76  | 1000 | 0.2748          | 0.9444   |
| 0.1777        | 1.85  | 1050 | 0.3463          | 0.9206   |
| 0.1777        | 1.93  | 1100 | 0.2951          | 0.9444   |
| 0.1777        | 2.02  | 1150 | 0.2726          | 0.9524   |
| 0.1777        | 2.11  | 1200 | 0.3241          | 0.9444   |
| 0.1777        | 2.2   | 1250 | 0.3543          | 0.9365   |
| 0.1777        | 2.28  | 1300 | 0.4440          | 0.9444   |


### 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-6n", "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-6n
==========================


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: 0.2748
* Accuracy: 0.9444


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