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# ff_analysis_3

This model is a fine-tuned version of [zdreiosis/ff_analysis_2](https://huggingface.co/zdreiosis/ff_analysis_2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0060
- F1: 1.0
- Roc Auc: 1.0
- Accuracy: 1.0

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.02  | 50   | 0.0138          | 1.0    | 1.0     | 1.0      |
| No log        | 2.04  | 100  | 0.0132          | 0.9966 | 0.9966  | 0.9885   |
| No log        | 3.06  | 150  | 0.0097          | 1.0    | 1.0     | 1.0      |
| No log        | 4.08  | 200  | 0.0095          | 0.9966 | 0.9966  | 0.9885   |
| No log        | 5.1   | 250  | 0.0096          | 1.0    | 1.0     | 1.0      |
| No log        | 6.12  | 300  | 0.0079          | 1.0    | 1.0     | 1.0      |
| No log        | 7.14  | 350  | 0.0070          | 1.0    | 1.0     | 1.0      |
| No log        | 8.16  | 400  | 0.0069          | 1.0    | 1.0     | 1.0      |
| No log        | 9.18  | 450  | 0.0065          | 1.0    | 1.0     | 1.0      |
| 0.012         | 10.2  | 500  | 0.0060          | 1.0    | 1.0     | 1.0      |
| 0.012         | 11.22 | 550  | 0.0060          | 0.9966 | 0.9966  | 0.9885   |
| 0.012         | 12.24 | 600  | 0.0054          | 1.0    | 1.0     | 1.0      |
| 0.012         | 13.27 | 650  | 0.0049          | 1.0    | 1.0     | 1.0      |
| 0.012         | 14.29 | 700  | 0.0048          | 1.0    | 1.0     | 1.0      |
| 0.012         | 15.31 | 750  | 0.0046          | 1.0    | 1.0     | 1.0      |
| 0.012         | 16.33 | 800  | 0.0042          | 1.0    | 1.0     | 1.0      |
| 0.012         | 17.35 | 850  | 0.0042          | 1.0    | 1.0     | 1.0      |
| 0.012         | 18.37 | 900  | 0.0040          | 1.0    | 1.0     | 1.0      |
| 0.012         | 19.39 | 950  | 0.0040          | 1.0    | 1.0     | 1.0      |
| 0.0046        | 20.41 | 1000 | 0.0038          | 1.0    | 1.0     | 1.0      |
| 0.0046        | 21.43 | 1050 | 0.0037          | 1.0    | 1.0     | 1.0      |
| 0.0046        | 22.45 | 1100 | 0.0039          | 1.0    | 1.0     | 1.0      |
| 0.0046        | 23.47 | 1150 | 0.0038          | 1.0    | 1.0     | 1.0      |
| 0.0046        | 24.49 | 1200 | 0.0035          | 1.0    | 1.0     | 1.0      |
| 0.0046        | 25.51 | 1250 | 0.0037          | 1.0    | 1.0     | 1.0      |
| 0.0046        | 26.53 | 1300 | 0.0034          | 1.0    | 1.0     | 1.0      |
| 0.0046        | 27.55 | 1350 | 0.0035          | 1.0    | 1.0     | 1.0      |
| 0.0046        | 28.57 | 1400 | 0.0034          | 1.0    | 1.0     | 1.0      |
| 0.0046        | 29.59 | 1450 | 0.0035          | 1.0    | 1.0     | 1.0      |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["6th", "generated_from_trainer"], "metrics": ["f1", "accuracy"], "model-index": [{"name": "ff_analysis_3", "results": []}]}
transformers pytorch tensorboard bert text-classification 6th generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #6th #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

ff\_analysis\_3
===============


This model is a fine-tuned version of zdreiosis/ff\_analysis\_2 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0060
* F1: 1.0
* Roc Auc: 1.0
* Accuracy: 1.0


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.15.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #6th #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #bert #text-classification #6th #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: linear
* num\_epochs: 30### Training results### Framework versions


* Transformers 4.15.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.10.3