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# small-mlm-snli-from-scratch-target-conll2003

This model is a fine-tuned version of [muhtasham/small-mlm-snli-from-scratch](https://huggingface.co/muhtasham/small-mlm-snli-from-scratch) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2722
- Precision: 0.6350
- Recall: 0.7334
- F1: 0.6807
- Accuracy: 0.9355

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- training_steps: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5969        | 1.14  | 500  | 0.4174          | 0.3902    | 0.4960 | 0.4368 | 0.8740   |
| 0.3356        | 2.28  | 1000 | 0.3105          | 0.4951    | 0.6070 | 0.5454 | 0.9055   |
| 0.2397        | 3.42  | 1500 | 0.2794          | 0.4914    | 0.6572 | 0.5624 | 0.9120   |
| 0.1822        | 4.56  | 2000 | 0.2548          | 0.5653    | 0.6718 | 0.6140 | 0.9241   |
| 0.1443        | 5.69  | 2500 | 0.2484          | 0.5930    | 0.6816 | 0.6342 | 0.9280   |
| 0.1151        | 6.83  | 3000 | 0.2457          | 0.5781    | 0.7060 | 0.6357 | 0.9291   |
| 0.0927        | 7.97  | 3500 | 0.2430          | 0.6057    | 0.7174 | 0.6569 | 0.9320   |
| 0.0739        | 9.11  | 4000 | 0.2645          | 0.6313    | 0.7078 | 0.6674 | 0.9349   |
| 0.0606        | 10.25 | 4500 | 0.2651          | 0.6354    | 0.7218 | 0.6759 | 0.9359   |
| 0.0506        | 11.39 | 5000 | 0.2722          | 0.6350    | 0.7334 | 0.6807 | 0.9355   |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "small-mlm-snli-from-scratch-target-conll2003", "results": []}]}
transformers pytorch bert token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

small-mlm-snli-from-scratch-target-conll2003
============================================


This model is a fine-tuned version of muhtasham/small-mlm-snli-from-scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2722
* Precision: 0.6350
* Recall: 0.7334
* F1: 0.6807
* Accuracy: 0.9355


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: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* training\_steps: 5000


### Training results



### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* training\_steps: 5000 ### Training results ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* training\_steps: 5000 ### Training results ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* training\_steps: 5000### Training results### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2