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# film95000roberta-base


## 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
- training_steps: 14840

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.5804        | 0.34  | 500   | 2.4511          |
| 2.5301        | 0.67  | 1000  | 2.4079          |
| 2.4702        | 1.01  | 1500  | 2.3465          |
| 2.4039        | 1.35  | 2000  | 2.2871          |
| 2.3628        | 1.68  | 2500  | 2.2480          |
| 2.3216        | 2.02  | 3000  | 2.2253          |
| 2.259         | 2.36  | 3500  | 2.1989          |
| 2.2392        | 2.69  | 4000  | 2.1679          |
| 2.2156        | 3.03  | 4500  | 2.1489          |
| 2.17          | 3.37  | 5000  | 2.1207          |
| 2.1497        | 3.7   | 5500  | 2.1003          |
| 2.1281        | 4.04  | 6000  | 2.0753          |
| 2.0873        | 4.38  | 6500  | 2.0626          |
| 2.0658        | 4.71  | 7000  | 2.0411          |
| 2.0446        | 5.05  | 7500  | 2.0332          |
| 2.0091        | 5.39  | 8000  | 2.0082          |
| 1.9974        | 5.72  | 8500  | 1.9966          |
| 1.9802        | 6.06  | 9000  | 1.9752          |
| 1.9498        | 6.4   | 9500  | 1.9578          |
| 1.9426        | 6.73  | 10000 | 1.9451          |
| 1.9199        | 7.07  | 10500 | 1.9226          |
| 1.8933        | 7.41  | 11000 | 1.9161          |
| 1.8836        | 7.74  | 11500 | 1.8952          |
| 1.8625        | 8.08  | 12000 | 1.8846          |
| 1.8405        | 8.42  | 12500 | 1.8810          |
| 1.8311        | 8.75  | 13000 | 1.8703          |
| 1.8187        | 9.09  | 13500 | 1.8634          |
| 1.804         | 9.43  | 14000 | 1.8441          |
| 1.7908        | 9.76  | 14500 | 1.8436          |


### Framework versions

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

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "film95000roberta-base", "results": []}]}
transformers pytorch tensorboard roberta fill-mask generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

film95000roberta-base
=====================


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
* training\_steps: 14840


### 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
* training\_steps: 14840 ### 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 #roberta #fill-mask #generated_from_trainer #license-mit #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
* training\_steps: 14840 ### 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 #roberta #fill-mask #generated_from_trainer #license-mit #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
* training\_steps: 14840### Training results### Framework versions


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