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# ec_classfication_0502_distilbert_base_uncased

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9120
- F1: 0.8222

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 59   | 0.6145          | 0.5753 |
| No log        | 2.0   | 118  | 0.5000          | 0.7619 |
| No log        | 3.0   | 177  | 0.5990          | 0.7    |
| No log        | 4.0   | 236  | 0.5030          | 0.8235 |
| No log        | 5.0   | 295  | 0.6379          | 0.8478 |
| No log        | 6.0   | 354  | 0.6739          | 0.8478 |
| No log        | 7.0   | 413  | 0.7597          | 0.8090 |
| No log        | 8.0   | 472  | 0.7854          | 0.8222 |
| 0.1878        | 9.0   | 531  | 0.8594          | 0.8222 |
| 0.1878        | 10.0  | 590  | 0.8947          | 0.8090 |
| 0.1878        | 11.0  | 649  | 0.9086          | 0.8222 |
| 0.1878        | 12.0  | 708  | 0.9130          | 0.8222 |
| 0.1878        | 13.0  | 767  | 0.9070          | 0.8222 |
| 0.1878        | 14.0  | 826  | 0.9117          | 0.8222 |
| 0.1878        | 15.0  | 885  | 0.9120          | 0.8222 |


### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "ec_classfication_0502_distilbert_base_uncased", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

ec\_classfication\_0502\_distilbert\_base\_uncased
==================================================


This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.9120
* F1: 0.8222


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


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.2



### 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 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #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 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.2