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# film20000bert-base-uncased

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0507

## 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: 0.0002
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| No log        | 1.0   | 313   | 2.4018          |
| 2.5523        | 2.0   | 626   | 2.3561          |
| 2.5523        | 3.0   | 939   | 2.3207          |
| 2.3635        | 4.0   | 1252  | 2.2873          |
| 2.236         | 5.0   | 1565  | 2.2714          |
| 2.236         | 6.0   | 1878  | 2.2388          |
| 2.14          | 7.0   | 2191  | 2.2375          |
| 2.0598        | 8.0   | 2504  | 2.2085          |
| 2.0598        | 9.0   | 2817  | 2.2044          |
| 1.9831        | 10.0  | 3130  | 2.1849          |
| 1.9831        | 11.0  | 3443  | 2.1806          |
| 1.9281        | 12.0  | 3756  | 2.1785          |
| 1.8663        | 13.0  | 4069  | 2.1622          |
| 1.8663        | 14.0  | 4382  | 2.1529          |
| 1.802         | 15.0  | 4695  | 2.1696          |
| 1.7597        | 16.0  | 5008  | 2.1453          |
| 1.7597        | 17.0  | 5321  | 2.1361          |
| 1.7017        | 18.0  | 5634  | 2.1388          |
| 1.7017        | 19.0  | 5947  | 2.1174          |
| 1.6644        | 20.0  | 6260  | 2.1047          |
| 1.6194        | 21.0  | 6573  | 2.1235          |
| 1.6194        | 22.0  | 6886  | 2.1033          |
| 1.5795        | 23.0  | 7199  | 2.0899          |
| 1.5431        | 24.0  | 7512  | 2.0995          |
| 1.5431        | 25.0  | 7825  | 2.0889          |
| 1.5081        | 26.0  | 8138  | 2.0946          |
| 1.5081        | 27.0  | 8451  | 2.0816          |
| 1.4755        | 28.0  | 8764  | 2.0935          |
| 1.4379        | 29.0  | 9077  | 2.0709          |
| 1.4379        | 30.0  | 9390  | 2.0708          |
| 1.4048        | 31.0  | 9703  | 2.0817          |
| 1.3761        | 32.0  | 10016 | 2.0695          |
| 1.3761        | 33.0  | 10329 | 2.0525          |
| 1.3536        | 34.0  | 10642 | 2.0750          |
| 1.3536        | 35.0  | 10955 | 2.0721          |
| 1.3358        | 36.0  | 11268 | 2.0783          |
| 1.3147        | 37.0  | 11581 | 2.0731          |
| 1.3147        | 38.0  | 11894 | 2.0577          |
| 1.2948        | 39.0  | 12207 | 2.0403          |
| 1.2884        | 40.0  | 12520 | 2.0217          |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "film20000bert-base-uncased", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

film20000bert-base-uncased
==========================


This model is a fine-tuned version of bert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0507


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: 0.0002
* 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
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 40


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* 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
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 40 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* 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
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 40 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* 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
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 40### Training results### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2