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# rubert-tiny2_finetuned_emotion_experiment_modified_CE_LOSS_resampling

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: 0.4520
- Accuracy: 0.8621
- F1: 0.8616

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.1134        | 1.0   | 53   | 0.9494          | 0.7716   | 0.7555 |
| 0.8421        | 2.0   | 106  | 0.7092          | 0.8204   | 0.8172 |
| 0.6488        | 3.0   | 159  | 0.6000          | 0.8319   | 0.8313 |
| 0.5392        | 4.0   | 212  | 0.5368          | 0.8376   | 0.8392 |
| 0.4616        | 5.0   | 265  | 0.4951          | 0.8549   | 0.8544 |
| 0.4138        | 6.0   | 318  | 0.4743          | 0.8621   | 0.8615 |
| 0.3694        | 7.0   | 371  | 0.4607          | 0.8563   | 0.8581 |
| 0.3375        | 8.0   | 424  | 0.4469          | 0.8693   | 0.8697 |
| 0.3049        | 9.0   | 477  | 0.4412          | 0.8649   | 0.8670 |
| 0.2804        | 10.0  | 530  | 0.4469          | 0.8635   | 0.8637 |
| 0.2787        | 11.0  | 583  | 0.4471          | 0.8693   | 0.8683 |
| 0.2284        | 12.0  | 636  | 0.4474          | 0.8693   | 0.8694 |
| 0.2188        | 13.0  | 689  | 0.4530          | 0.8649   | 0.8643 |
| 0.1998        | 14.0  | 742  | 0.4520          | 0.8621   | 0.8616 |


### 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_modified_CE_LOSS_resampling", "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\_modified\_CE\_LOSS\_resampling
============================================================================


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: 0.4520
* Accuracy: 0.8621
* F1: 0.8616


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