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# canine_sent_2304v1

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: 0.0000
- Precision: 1.0
- Recall: 1.0
- F1: 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0218        | 1.0   | 781   | 0.0051          | 0.9531    | 0.9434 | 0.9482 | 0.9980   |
| 0.0059        | 2.0   | 1562  | 0.0028          | 0.9712    | 0.9714 | 0.9713 | 0.9989   |
| 0.0043        | 3.0   | 2343  | 0.0018          | 0.9733    | 0.9980 | 0.9855 | 0.9994   |
| 0.0021        | 4.0   | 3124  | 0.0010          | 0.9873    | 0.9991 | 0.9932 | 0.9997   |
| 0.0018        | 5.0   | 3905  | 0.0005          | 0.9952    | 0.9984 | 0.9968 | 0.9998   |
| 0.0012        | 6.0   | 4686  | 0.0002          | 0.9988    | 0.9986 | 0.9987 | 0.9999   |
| 0.0007        | 7.0   | 5467  | 0.0001          | 0.9989    | 0.9986 | 0.9988 | 1.0000   |
| 0.0007        | 8.0   | 6248  | 0.0001          | 0.9998    | 0.9991 | 0.9995 | 1.0000   |
| 0.0004        | 9.0   | 7029  | 0.0000          | 0.9998    | 1.0    | 0.9999 | 1.0000   |
| 0.0004        | 10.0  | 7810  | 0.0000          | 0.9998    | 0.9995 | 0.9996 | 1.0000   |
| 0.0003        | 11.0  | 8591  | 0.0001          | 0.9996    | 0.9998 | 0.9997 | 1.0000   |
| 0.0002        | 12.0  | 9372  | 0.0000          | 1.0       | 0.9998 | 0.9999 | 1.0000   |
| 0.0002        | 13.0  | 10153 | 0.0000          | 1.0       | 0.9998 | 0.9999 | 1.0000   |
| 0.0001        | 14.0  | 10934 | 0.0000          | 1.0       | 0.9998 | 0.9999 | 1.0000   |
| 0.0001        | 15.0  | 11715 | 0.0000          | 1.0       | 1.0    | 1.0    | 1.0      |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "canine_sent_2304v1", "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\_sent\_2304v1
====================


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: 0.0000
* Precision: 1.0
* Recall: 1.0
* F1: 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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* 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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* 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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3