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# canine_deasciifier_0305

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: 0.0007
- Precision: 0.9978
- Recall: 0.9983
- F1: 0.9981
- Accuracy: 0.9998

## 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  | 0.0672          | 0.7433    | 0.8204 | 0.7800 | 0.9735   |
| No log        | 2.0   | 488  | 0.0445          | 0.8205    | 0.8889 | 0.8533 | 0.9832   |
| 0.1401        | 3.0   | 732  | 0.0256          | 0.8950    | 0.9259 | 0.9102 | 0.9906   |
| 0.1401        | 4.0   | 976  | 0.0165          | 0.9384    | 0.9483 | 0.9433 | 0.9943   |
| 0.0364        | 5.0   | 1220 | 0.0112          | 0.9597    | 0.9629 | 0.9613 | 0.9962   |
| 0.0364        | 6.0   | 1464 | 0.0089          | 0.9656    | 0.9736 | 0.9696 | 0.9970   |
| 0.021         | 7.0   | 1708 | 0.0073          | 0.9710    | 0.9797 | 0.9753 | 0.9976   |
| 0.021         | 8.0   | 1952 | 0.0060          | 0.9740    | 0.9838 | 0.9789 | 0.9980   |
| 0.0139        | 9.0   | 2196 | 0.0038          | 0.9856    | 0.9890 | 0.9873 | 0.9988   |
| 0.0139        | 10.0  | 2440 | 0.0030          | 0.9893    | 0.9912 | 0.9903 | 0.9991   |
| 0.01          | 11.0  | 2684 | 0.0024          | 0.9916    | 0.9932 | 0.9924 | 0.9993   |
| 0.01          | 12.0  | 2928 | 0.0021          | 0.9919    | 0.9941 | 0.9930 | 0.9993   |
| 0.0072        | 13.0  | 3172 | 0.0018          | 0.9938    | 0.9957 | 0.9947 | 0.9995   |
| 0.0072        | 14.0  | 3416 | 0.0016          | 0.9940    | 0.9958 | 0.9949 | 0.9995   |
| 0.0056        | 15.0  | 3660 | 0.0012          | 0.9955    | 0.9968 | 0.9962 | 0.9996   |
| 0.0056        | 16.0  | 3904 | 0.0012          | 0.9954    | 0.9969 | 0.9962 | 0.9996   |
| 0.0045        | 17.0  | 4148 | 0.0008          | 0.9975    | 0.9979 | 0.9977 | 0.9998   |
| 0.0045        | 18.0  | 4392 | 0.0008          | 0.9975    | 0.9981 | 0.9978 | 0.9998   |
| 0.0039        | 19.0  | 4636 | 0.0008          | 0.9974    | 0.9981 | 0.9977 | 0.9998   |
| 0.0039        | 20.0  | 4880 | 0.0007          | 0.9978    | 0.9983 | 0.9981 | 0.9998   |


### 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_0305", "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\_0305
=========================


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: 0.0007
* Precision: 0.9978
* Recall: 0.9983
* F1: 0.9981
* Accuracy: 0.9998


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