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# bert-base-uncased-imdb

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4942
- Accuracy: 0.9126

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1546
- training_steps: 15468

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3952        | 0.65  | 2000  | 0.4012          | 0.86     |
| 0.2954        | 1.29  | 4000  | 0.4535          | 0.892    |
| 0.2595        | 1.94  | 6000  | 0.4320          | 0.892    |
| 0.1516        | 2.59  | 8000  | 0.5309          | 0.896    |
| 0.1167        | 3.23  | 10000 | 0.4070          | 0.928    |
| 0.0624        | 3.88  | 12000 | 0.5055          | 0.908    |
| 0.0329        | 4.52  | 14000 | 0.4342          | 0.92     |


### Framework versions

- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.6.1
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer", "sibyl"], "datasets": ["imdb"], "metrics": ["accuracy"], "model-index": [{"name": "bert-base-uncased-imdb", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "imdb", "type": "imdb", "args": "plain_text"}, "metrics": [{"type": "accuracy", "value": 0.91264, "name": "Accuracy"}]}]}]}
transformers pytorch bert text-classification generated_from_trainer sibyl dataset:imdb license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #sibyl #dataset-imdb #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

bert-base-uncased-imdb
======================


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


* Loss: 0.4942
* Accuracy: 0.9126


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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1546
* training\_steps: 15468


### Training results



### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.6.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1546
* training\_steps: 15468 ### Training results ### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.6.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #sibyl #dataset-imdb #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1546
* training\_steps: 15468 ### Training results ### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.6.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #sibyl #dataset-imdb #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1546
* training\_steps: 15468### Training results### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.6.1
* Tokenizers 0.10.3