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

This model is a fine-tuned version of [muhtasham/small-mlm-snli-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/small-mlm-snli-from-scratch-custom-tokenizer) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3378
- Precision: 0.4244
- Recall: 0.5441
- F1: 0.4768
- Accuracy: 0.8956

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7215        | 1.14  | 500  | 0.5706          | 0.1492    | 0.2666 | 0.1913 | 0.8173   |
| 0.5251        | 2.28  | 1000 | 0.4653          | 0.2138    | 0.3122 | 0.2538 | 0.8465   |
| 0.4538        | 3.42  | 1500 | 0.4361          | 0.2118    | 0.4010 | 0.2772 | 0.8472   |
| 0.3962        | 4.56  | 2000 | 0.3844          | 0.2868    | 0.4187 | 0.3404 | 0.8677   |
| 0.356         | 5.69  | 2500 | 0.3705          | 0.3088    | 0.4731 | 0.3737 | 0.8702   |
| 0.3256        | 6.83  | 3000 | 0.3540          | 0.3297    | 0.4798 | 0.3908 | 0.8790   |
| 0.2923        | 7.97  | 3500 | 0.3442          | 0.3762    | 0.4845 | 0.4235 | 0.8851   |
| 0.2599        | 9.11  | 4000 | 0.3410          | 0.3992    | 0.5101 | 0.4479 | 0.8904   |
| 0.2345        | 10.25 | 4500 | 0.3375          | 0.4118    | 0.5279 | 0.4627 | 0.8928   |
| 0.2119        | 11.39 | 5000 | 0.3378          | 0.4244    | 0.5441 | 0.4768 | 0.8956   |


### 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-custom-tokenizer-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-custom-tokenizer-target-conll2003
=============================================================


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


* Loss: 0.3378
* Precision: 0.4244
* Recall: 0.5441
* F1: 0.4768
* Accuracy: 0.8956


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