
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# deberta-v2-base-japanese-finetuned-kyoto

This model is a fine-tuned version of [ku-nlp/deberta-v2-base-japanese](https://huggingface.co/ku-nlp/deberta-v2-base-japanese) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6094
- Precision: 0.7567
- Recall: 0.7654
- F1: 0.7574

## 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: 120
- eval_batch_size: 120
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| No log        | 1.0   | 21   | 0.7848          | 0.7113    | 0.5890 | 0.4384 |
| No log        | 2.0   | 42   | 0.6595          | 0.6998    | 0.7330 | 0.7159 |
| No log        | 3.0   | 63   | 0.6561          | 0.7189    | 0.7136 | 0.7007 |
| No log        | 4.0   | 84   | 0.6023          | 0.7166    | 0.7508 | 0.7333 |
| No log        | 5.0   | 105  | 0.6213          | 0.7325    | 0.7427 | 0.7283 |
| No log        | 6.0   | 126  | 0.6261          | 0.7652    | 0.7460 | 0.7349 |
| No log        | 7.0   | 147  | 0.5984          | 0.7602    | 0.7540 | 0.7481 |
| No log        | 8.0   | 168  | 0.6204          | 0.7642    | 0.7573 | 0.7507 |
| No log        | 9.0   | 189  | 0.6094          | 0.7567    | 0.7654 | 0.7574 |
| No log        | 10.0  | 210  | 0.6167          | 0.7609    | 0.7605 | 0.7554 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "cc-by-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1"], "model-index": [{"name": "deberta-v2-base-japanese-finetuned-kyoto", "results": []}]}
transformers pytorch tensorboard deberta-v2 text-classification generated_from_trainer license:cc-by-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #deberta-v2 #text-classification #generated_from_trainer #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 

deberta-v2-base-japanese-finetuned-kyoto
========================================


This model is a fine-tuned version of ku-nlp/deberta-v2-base-japanese on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.6094
* Precision: 0.7567
* Recall: 0.7654
* F1: 0.7574


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: 120
* eval\_batch\_size: 120
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 120
* eval\_batch\_size: 120
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #deberta-v2 #text-classification #generated_from_trainer #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 120
* eval\_batch\_size: 120
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #deberta-v2 #text-classification #generated_from_trainer #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 120
* eval\_batch\_size: 120
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2