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# roberta-base-mnli_ChcE

This model is a fine-tuned version of [WillHeld/roberta-base-mnli](https://huggingface.co/WillHeld/roberta-base-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7094
- Acc: 0.8698

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Acc    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.3102        | 0.17  | 2000  | 0.4135          | 0.8545 |
| 0.3046        | 0.33  | 4000  | 0.4024          | 0.8645 |
| 0.3038        | 0.5   | 6000  | 0.3936          | 0.8668 |
| 0.3012        | 0.67  | 8000  | 0.4007          | 0.8625 |
| 0.2979        | 0.83  | 10000 | 0.4235          | 0.8620 |
| 0.2997        | 1.0   | 12000 | 0.4031          | 0.8644 |
| 0.2099        | 1.17  | 14000 | 0.4393          | 0.8633 |
| 0.2114        | 1.33  | 16000 | 0.4662          | 0.8628 |
| 0.2147        | 1.5   | 18000 | 0.4331          | 0.8648 |
| 0.2122        | 1.67  | 20000 | 0.4166          | 0.8702 |
| 0.2156        | 1.83  | 22000 | 0.4463          | 0.8633 |
| 0.2117        | 2.0   | 24000 | 0.4637          | 0.8680 |
| 0.1469        | 2.17  | 26000 | 0.5211          | 0.8681 |
| 0.1526        | 2.33  | 28000 | 0.5206          | 0.8620 |
| 0.1494        | 2.5   | 30000 | 0.5168          | 0.8664 |
| 0.1519        | 2.67  | 32000 | 0.4830          | 0.8700 |
| 0.152         | 2.84  | 34000 | 0.5465          | 0.8636 |
| 0.1498        | 3.0   | 36000 | 0.5550          | 0.8680 |
| 0.1131        | 3.17  | 38000 | 0.6764          | 0.8602 |
| 0.1135        | 3.34  | 40000 | 0.6200          | 0.8657 |
| 0.1175        | 3.5   | 42000 | 0.5889          | 0.8671 |
| 0.1156        | 3.67  | 44000 | 0.6300          | 0.8663 |
| 0.1104        | 3.84  | 46000 | 0.6045          | 0.8690 |
| 0.1111        | 4.0   | 48000 | 0.6413          | 0.8694 |
| 0.086         | 4.17  | 50000 | 0.7271          | 0.8658 |
| 0.0895        | 4.34  | 52000 | 0.7274          | 0.8683 |
| 0.0867        | 4.5   | 54000 | 0.7226          | 0.8658 |
| 0.0886        | 4.67  | 56000 | 0.7182          | 0.8691 |
| 0.0849        | 4.84  | 58000 | 0.7094          | 0.8698 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "roberta-base-mnli_ChcE", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

roberta-base-mnli\_ChcE
=======================


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


* Loss: 0.7094
* Acc: 0.8698


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.24.0
* Pytorch 1.13.0+cu117
* Datasets 2.7.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.13.0+cu117
* Datasets 2.7.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.13.0+cu117
* Datasets 2.7.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.24.0
* Pytorch 1.13.0+cu117
* Datasets 2.7.1
* Tokenizers 0.12.1