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# rubert-tiny2_finetuned_emotion_experiment_augmented_anger_fear

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: 0.4049
- Accuracy: 0.8779
- F1: 0.8775

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.3097        | 1.0   | 69   | 1.1369          | 0.6628   | 0.6210 |
| 0.949         | 2.0   | 138  | 0.7114          | 0.8225   | 0.8202 |
| 0.6288        | 3.0   | 207  | 0.5147          | 0.8507   | 0.8494 |
| 0.4724        | 4.0   | 276  | 0.4424          | 0.8643   | 0.8634 |
| 0.3912        | 5.0   | 345  | 0.4149          | 0.8653   | 0.8645 |
| 0.3283        | 6.0   | 414  | 0.3982          | 0.8664   | 0.8656 |
| 0.3015        | 7.0   | 483  | 0.3958          | 0.8685   | 0.8676 |
| 0.269         | 8.0   | 552  | 0.3888          | 0.8716   | 0.8712 |
| 0.2366        | 9.0   | 621  | 0.3909          | 0.8747   | 0.8742 |
| 0.2241        | 10.0  | 690  | 0.3991          | 0.8716   | 0.8707 |
| 0.1972        | 11.0  | 759  | 0.3984          | 0.8727   | 0.8720 |
| 0.1765        | 12.0  | 828  | 0.3940          | 0.8758   | 0.8753 |
| 0.1582        | 13.0  | 897  | 0.4049          | 0.8779   | 0.8775 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "rubert-tiny2_finetuned_emotion_experiment_augmented_anger_fear", "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\_augmented\_anger\_fear
====================================================================


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: 0.4049
* Accuracy: 0.8779
* F1: 0.8775


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: 40


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* 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: 40 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* 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: 40 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* 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: 40### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1