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

This model is a fine-tuned version of [muhtasham/small-mlm-rotten_tomatoes-from-scratch](https://huggingface.co/muhtasham/small-mlm-rotten_tomatoes-from-scratch) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2814
- Precision: 0.5816
- Recall: 0.7099
- F1: 0.6394
- Accuracy: 0.9299

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6075        | 1.14  | 500  | 0.4273          | 0.3917    | 0.4366 | 0.4129 | 0.8743   |
| 0.3582        | 2.28  | 1000 | 0.3436          | 0.4459    | 0.5478 | 0.4916 | 0.8969   |
| 0.2718        | 3.42  | 1500 | 0.3134          | 0.4499    | 0.6254 | 0.5233 | 0.9032   |
| 0.2142        | 4.56  | 2000 | 0.2927          | 0.4969    | 0.6298 | 0.5555 | 0.9122   |
| 0.1751        | 5.69  | 2500 | 0.2815          | 0.5500    | 0.6570 | 0.5988 | 0.9192   |
| 0.1468        | 6.83  | 3000 | 0.2693          | 0.5472    | 0.6930 | 0.6115 | 0.9221   |
| 0.119         | 7.97  | 3500 | 0.2669          | 0.5506    | 0.6880 | 0.6117 | 0.9245   |
| 0.0959        | 9.11  | 4000 | 0.2817          | 0.5691    | 0.6747 | 0.6174 | 0.9267   |
| 0.0804        | 10.25 | 4500 | 0.2860          | 0.5572    | 0.7065 | 0.6230 | 0.9251   |
| 0.0687        | 11.39 | 5000 | 0.2814          | 0.5816    | 0.7099 | 0.6394 | 0.9299   |


### 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-rotten_tomatoes-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-rotten\_tomatoes-from-scratch-target-conll2003
========================================================


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


* Loss: 0.2814
* Precision: 0.5816
* Recall: 0.7099
* F1: 0.6394
* Accuracy: 0.9299


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