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# fb-data2vec-finetuned-finance-classification

This model is a fine-tuned version of [facebook/data2vec-text-base](https://huggingface.co/facebook/data2vec-text-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8993
- Accuracy: 0.8557
- F1: 0.8563
- Precision: 0.8576
- Recall: 0.8557

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 285  | 0.6704          | 0.6680   | 0.6262 | 0.7919    | 0.6680 |
| 0.6626        | 2.0   | 570  | 0.4731          | 0.8360   | 0.8350 | 0.8346    | 0.8360 |
| 0.6626        | 3.0   | 855  | 0.4598          | 0.8458   | 0.8454 | 0.8452    | 0.8458 |
| 0.3666        | 4.0   | 1140 | 0.4758          | 0.8360   | 0.8352 | 0.8353    | 0.8360 |
| 0.3666        | 5.0   | 1425 | 0.5683          | 0.8340   | 0.8342 | 0.8353    | 0.8340 |
| 0.2316        | 6.0   | 1710 | 0.6234          | 0.8419   | 0.8421 | 0.8447    | 0.8419 |
| 0.2316        | 7.0   | 1995 | 0.7186          | 0.8379   | 0.8385 | 0.8395    | 0.8379 |
| 0.1523        | 8.0   | 2280 | 0.7268          | 0.8439   | 0.8442 | 0.8455    | 0.8439 |
| 0.0928        | 9.0   | 2565 | 0.7364          | 0.8439   | 0.8452 | 0.8494    | 0.8439 |
| 0.0928        | 10.0  | 2850 | 0.7975          | 0.8478   | 0.8476 | 0.8476    | 0.8478 |
| 0.054         | 11.0  | 3135 | 0.9019          | 0.8498   | 0.8509 | 0.8554    | 0.8498 |
| 0.054         | 12.0  | 3420 | 0.8779          | 0.8538   | 0.8548 | 0.8578    | 0.8538 |
| 0.036         | 13.0  | 3705 | 0.8914          | 0.8617   | 0.8626 | 0.8652    | 0.8617 |
| 0.036         | 14.0  | 3990 | 0.8976          | 0.8538   | 0.8547 | 0.8572    | 0.8538 |
| 0.0232        | 15.0  | 4275 | 0.8993          | 0.8557   | 0.8563 | 0.8576    | 0.8557 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "fb-data2vec-finetuned-finance-classification", "results": []}]}
transformers pytorch tensorboard data2vec-text text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #data2vec-text #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

fb-data2vec-finetuned-finance-classification
============================================


This model is a fine-tuned version of facebook/data2vec-text-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.8993
* Accuracy: 0.8557
* F1: 0.8563
* Precision: 0.8576
* Recall: 0.8557


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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #data2vec-text #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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #data2vec-text #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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1