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# rubert-tiny2_finetuned_emotion_experiment

This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3947
- Accuracy: 0.8616
- F1: 0.8577

## 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: 64
- eval_batch_size: 64
- 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 | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.651         | 1.0   | 54   | 0.5689          | 0.8172   | 0.8008 |
| 0.5355        | 2.0   | 108  | 0.4842          | 0.8486   | 0.8349 |
| 0.4561        | 3.0   | 162  | 0.4436          | 0.8590   | 0.8509 |
| 0.4133        | 4.0   | 216  | 0.4203          | 0.8590   | 0.8528 |
| 0.3709        | 5.0   | 270  | 0.4071          | 0.8564   | 0.8515 |
| 0.3346        | 6.0   | 324  | 0.3980          | 0.8564   | 0.8529 |
| 0.3153        | 7.0   | 378  | 0.3985          | 0.8590   | 0.8565 |
| 0.302         | 8.0   | 432  | 0.3967          | 0.8642   | 0.8619 |
| 0.2774        | 9.0   | 486  | 0.3958          | 0.8616   | 0.8575 |
| 0.2728        | 10.0  | 540  | 0.3959          | 0.8668   | 0.8644 |
| 0.2427        | 11.0  | 594  | 0.3962          | 0.8590   | 0.8550 |
| 0.2425        | 12.0  | 648  | 0.3959          | 0.8642   | 0.8611 |
| 0.2414        | 13.0  | 702  | 0.3959          | 0.8642   | 0.8611 |
| 0.2249        | 14.0  | 756  | 0.3949          | 0.8616   | 0.8582 |
| 0.2391        | 15.0  | 810  | 0.3947          | 0.8616   | 0.8577 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "rubert-tiny2_finetuned_emotion_experiment", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

rubert-tiny2\_finetuned\_emotion\_experiment
============================================


This model is a fine-tuned version of cointegrated/rubert-tiny2 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3947
* Accuracy: 0.8616
* F1: 0.8577


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: 64
* eval\_batch\_size: 64
* 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 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* 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 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* 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 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* 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 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1