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# canine_deasciifier_0205

This model is a fine-tuned version of [google/canine-s](https://huggingface.co/google/canine-s) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0004
- Precision: 0.9983
- Recall: 0.9991
- F1: 0.9987
- Accuracy: 0.9999

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 244  | 0.0462          | 0.8117    | 0.8638 | 0.8370 | 0.9829   |
| No log        | 2.0   | 488  | 0.0335          | 0.8432    | 0.9286 | 0.8838 | 0.9878   |
| 0.1144        | 3.0   | 732  | 0.0173          | 0.9182    | 0.9569 | 0.9371 | 0.9939   |
| 0.1144        | 4.0   | 976  | 0.0101          | 0.9567    | 0.9705 | 0.9636 | 0.9966   |
| 0.0241        | 5.0   | 1220 | 0.0067          | 0.9716    | 0.9786 | 0.9751 | 0.9978   |
| 0.0241        | 6.0   | 1464 | 0.0049          | 0.9784    | 0.9846 | 0.9815 | 0.9984   |
| 0.0137        | 7.0   | 1708 | 0.0039          | 0.9830    | 0.9886 | 0.9858 | 0.9987   |
| 0.0137        | 8.0   | 1952 | 0.0030          | 0.9870    | 0.9911 | 0.9891 | 0.9990   |
| 0.0088        | 9.0   | 2196 | 0.0024          | 0.9893    | 0.9933 | 0.9913 | 0.9992   |
| 0.0088        | 10.0  | 2440 | 0.0019          | 0.9916    | 0.9947 | 0.9932 | 0.9994   |
| 0.0061        | 11.0  | 2684 | 0.0013          | 0.9941    | 0.9962 | 0.9952 | 0.9996   |
| 0.0061        | 12.0  | 2928 | 0.0010          | 0.9955    | 0.9971 | 0.9963 | 0.9997   |
| 0.0045        | 13.0  | 3172 | 0.0010          | 0.9952    | 0.9973 | 0.9963 | 0.9997   |
| 0.0045        | 14.0  | 3416 | 0.0008          | 0.9966    | 0.9980 | 0.9973 | 0.9998   |
| 0.0033        | 15.0  | 3660 | 0.0006          | 0.9973    | 0.9982 | 0.9978 | 0.9998   |
| 0.0033        | 16.0  | 3904 | 0.0006          | 0.9975    | 0.9986 | 0.9980 | 0.9998   |
| 0.0027        | 17.0  | 4148 | 0.0004          | 0.9982    | 0.9988 | 0.9985 | 0.9999   |
| 0.0027        | 18.0  | 4392 | 0.0004          | 0.9982    | 0.9990 | 0.9986 | 0.9999   |
| 0.0023        | 19.0  | 4636 | 0.0004          | 0.9984    | 0.9991 | 0.9988 | 0.9999   |
| 0.0023        | 20.0  | 4880 | 0.0004          | 0.9983    | 0.9991 | 0.9987 | 0.9999   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "canine_deasciifier_0205", "results": []}]}
transformers pytorch tensorboard canine token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #canine #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

canine\_deasciifier\_0205
=========================


This model is a fine-tuned version of google/canine-s on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0004
* Precision: 0.9983
* Recall: 0.9991
* F1: 0.9987
* Accuracy: 0.9999


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: 20


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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: 20 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #canine #token-classification #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: 20 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3