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# distilbert-allsides

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: 0.9138
- Acc: 0.7094

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 12345
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 16
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Acc    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7667        | 1.0   | 822  | 0.7003          | 0.6820 |
| 0.6893        | 2.0   | 1644 | 0.6619          | 0.6981 |
| 0.6177        | 3.0   | 2466 | 0.6736          | 0.7064 |
| 0.595         | 4.0   | 3288 | 0.6642          | 0.7091 |
| 0.5179        | 5.0   | 4110 | 0.6936          | 0.7121 |
| 0.4698        | 6.0   | 4932 | 0.7670          | 0.7106 |
| 0.463         | 7.0   | 5754 | 0.8537          | 0.7121 |
| 0.4345        | 8.0   | 6576 | 0.9138          | 0.7094 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.1
- Datasets 1.17.0
- Tokenizers 0.10.3

{"license": "other", "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-allsides", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer license:other autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-other #autotrain_compatible #endpoints_compatible #region-us 

distilbert-allsides
===================


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: 0.9138
* Acc: 0.7094


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: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 12345
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 16
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.1
* Datasets 1.17.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 12345
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 16
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.1
* Datasets 1.17.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-other #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 12345
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 16
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.1
* Datasets 1.17.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-other #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 12345
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 16
* num\_epochs: 20
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.1
* Datasets 1.17.0
* Tokenizers 0.10.3