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

This model is a fine-tuned version of [muhtasham/tiny-mlm-snli-from-scratch-custom-tokenizer](https://huggingface.co/muhtasham/tiny-mlm-snli-from-scratch-custom-tokenizer) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4949
- Precision: 0.1811
- Recall: 0.2837
- F1: 0.2211
- Accuracy: 0.8401

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.1064        | 1.14  | 500  | 0.8667          | 0.0151    | 0.0165 | 0.0157 | 0.7660   |
| 0.7755        | 2.28  | 1000 | 0.7543          | 0.0452    | 0.0653 | 0.0534 | 0.7853   |
| 0.702         | 3.42  | 1500 | 0.6770          | 0.0724    | 0.1080 | 0.0867 | 0.8021   |
| 0.643         | 4.56  | 2000 | 0.6336          | 0.0973    | 0.1782 | 0.1259 | 0.8063   |
| 0.6062        | 5.69  | 2500 | 0.5967          | 0.1146    | 0.2020 | 0.1462 | 0.8143   |
| 0.5808        | 6.83  | 3000 | 0.5672          | 0.1282    | 0.2198 | 0.1619 | 0.8222   |
| 0.5564        | 7.97  | 3500 | 0.5431          | 0.1404    | 0.2450 | 0.1786 | 0.8270   |
| 0.5315        | 9.11  | 4000 | 0.5236          | 0.1478    | 0.2622 | 0.1891 | 0.8309   |
| 0.5137        | 10.25 | 4500 | 0.5095          | 0.1557    | 0.2777 | 0.1995 | 0.8338   |
| 0.4978        | 11.39 | 5000 | 0.4949          | 0.1811    | 0.2837 | 0.2211 | 0.8401   |


### 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": "tiny-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 

tiny-mlm-snli-from-scratch-custom-tokenizer-target-conll2003
============================================================


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


* Loss: 0.4949
* Precision: 0.1811
* Recall: 0.2837
* F1: 0.2211
* Accuracy: 0.8401


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