
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilroberta-base-finetuned-marktextepoch_35

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0029

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 35

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.5158        | 1.0   | 1500  | 2.3385          |
| 2.4312        | 2.0   | 3000  | 2.2620          |
| 2.3563        | 3.0   | 4500  | 2.2279          |
| 2.3249        | 4.0   | 6000  | 2.2165          |
| 2.2515        | 5.0   | 7500  | 2.2246          |
| 2.2178        | 6.0   | 9000  | 2.1714          |
| 2.1822        | 7.0   | 10500 | 2.1461          |
| 2.1501        | 8.0   | 12000 | 2.1388          |
| 2.1342        | 9.0   | 13500 | 2.1085          |
| 2.1141        | 10.0  | 15000 | 2.1090          |
| 2.0833        | 11.0  | 16500 | 2.1130          |
| 2.0769        | 12.0  | 18000 | 2.0969          |
| 2.0474        | 13.0  | 19500 | 2.0823          |
| 2.0364        | 14.0  | 21000 | 2.0893          |
| 2.0269        | 15.0  | 22500 | 2.0501          |
| 1.9814        | 16.0  | 24000 | 2.0667          |
| 1.9716        | 17.0  | 25500 | 2.0570          |
| 1.9611        | 18.0  | 27000 | 2.0530          |
| 1.9557        | 19.0  | 28500 | 2.0590          |
| 1.9443        | 20.0  | 30000 | 2.0381          |
| 1.9229        | 21.0  | 31500 | 2.0433          |
| 1.9192        | 22.0  | 33000 | 2.0468          |
| 1.8865        | 23.0  | 34500 | 2.0361          |
| 1.914         | 24.0  | 36000 | 2.0412          |
| 1.867         | 25.0  | 37500 | 2.0165          |
| 1.8724        | 26.0  | 39000 | 2.0152          |
| 1.8644        | 27.0  | 40500 | 2.0129          |
| 1.8685        | 28.0  | 42000 | 2.0183          |
| 1.8458        | 29.0  | 43500 | 2.0082          |
| 1.8653        | 30.0  | 45000 | 1.9939          |
| 1.8584        | 31.0  | 46500 | 2.0015          |
| 1.8396        | 32.0  | 48000 | 1.9924          |
| 1.8399        | 33.0  | 49500 | 2.0102          |
| 1.8363        | 34.0  | 51000 | 1.9946          |
| 1.83          | 35.0  | 52500 | 1.9908          |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "distilroberta-base-finetuned-marktextepoch_35", "results": []}]}
transformers pytorch tensorboard roberta fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilroberta-base-finetuned-marktextepoch\_35
==============================================


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


* Loss: 2.0029


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 35


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 35 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #roberta #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: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 35 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #roberta #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: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 35### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1