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# Wangchanberta-Depress-Finetuned

This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the wisesight_sentiment dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5910

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.0114        | 0.08  | 200   | 0.9538          |
| 0.8617        | 0.15  | 400   | 0.8280          |
| 0.7882        | 0.23  | 600   | 0.7472          |
| 0.7132        | 0.3   | 800   | 0.7264          |
| 0.7226        | 0.38  | 1000  | 0.7265          |
| 0.6854        | 0.45  | 1200  | 0.6792          |
| 0.621         | 0.53  | 1400  | 0.6451          |
| 0.6093        | 0.61  | 1600  | 0.6364          |
| 0.6099        | 0.68  | 1800  | 0.6128          |
| 0.5766        | 0.76  | 2000  | 0.6388          |
| 0.6033        | 0.83  | 2200  | 0.6148          |
| 0.5966        | 0.91  | 2400  | 0.6440          |
| 0.6208        | 0.98  | 2600  | 0.5910          |
| 0.5178        | 1.06  | 2800  | 0.6340          |
| 0.4863        | 1.13  | 3000  | 0.7177          |
| 0.4852        | 1.21  | 3200  | 0.6766          |
| 0.4711        | 1.29  | 3400  | 0.6739          |
| 0.5203        | 1.36  | 3600  | 0.6429          |
| 0.5167        | 1.44  | 3800  | 0.6539          |
| 0.5053        | 1.51  | 4000  | 0.6172          |
| 0.5076        | 1.59  | 4200  | 0.6053          |
| 0.4704        | 1.66  | 4400  | 0.6474          |
| 0.4807        | 1.74  | 4600  | 0.6225          |
| 0.4792        | 1.82  | 4800  | 0.6282          |
| 0.5177        | 1.89  | 5000  | 0.6011          |
| 0.4839        | 1.97  | 5200  | 0.6231          |
| 0.4155        | 2.04  | 5400  | 0.6668          |
| 0.3923        | 2.12  | 5600  | 0.6886          |
| 0.3713        | 2.19  | 5800  | 0.6895          |
| 0.364         | 2.27  | 6000  | 0.6886          |
| 0.3774        | 2.34  | 6200  | 0.7117          |
| 0.4001        | 2.42  | 6400  | 0.7081          |
| 0.3531        | 2.5   | 6600  | 0.7465          |
| 0.3768        | 2.57  | 6800  | 0.7706          |
| 0.3324        | 2.65  | 7000  | 0.7456          |
| 0.3597        | 2.72  | 7200  | 0.7507          |
| 0.3868        | 2.8   | 7400  | 0.7542          |
| 0.4141        | 2.87  | 7600  | 0.7223          |
| 0.3701        | 2.95  | 7800  | 0.7374          |
| 0.3175        | 3.03  | 8000  | 0.7615          |
| 0.2951        | 3.1   | 8200  | 0.7880          |
| 0.2885        | 3.18  | 8400  | 0.8158          |
| 0.2913        | 3.25  | 8600  | 0.8565          |
| 0.2815        | 3.33  | 8800  | 0.8649          |
| 0.2748        | 3.4   | 9000  | 0.8783          |
| 0.2776        | 3.48  | 9200  | 0.8851          |
| 0.2982        | 3.56  | 9400  | 0.8922          |
| 0.2939        | 3.63  | 9600  | 0.8796          |
| 0.2712        | 3.71  | 9800  | 0.8873          |
| 0.2918        | 3.78  | 10000 | 0.8973          |
| 0.3144        | 3.86  | 10200 | 0.8978          |
| 0.2988        | 3.93  | 10400 | 0.8951          |


### Framework versions

- Transformers 4.11.2
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "datasets": ["wisesight_sentiment"], "model-index": [{"name": "Wangchanberta-Depress-Finetuned", "results": []}]}
transformers pytorch tensorboard camembert text-classification generated_from_trainer dataset:wisesight_sentiment autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #camembert #text-classification #generated_from_trainer #dataset-wisesight_sentiment #autotrain_compatible #endpoints_compatible #region-us 

Wangchanberta-Depress-Finetuned
===============================


This model is a fine-tuned version of airesearch/wangchanberta-base-att-spm-uncased on the wisesight\_sentiment dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5910


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 400
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.11.2
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 400
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.11.2
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #camembert #text-classification #generated_from_trainer #dataset-wisesight_sentiment #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 400
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.11.2
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #camembert #text-classification #generated_from_trainer #dataset-wisesight_sentiment #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 400
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.11.2
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.10.3