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# smashing-sexism-robert-weighted-final-2

This model is a fine-tuned version of [readerbench/RoBERT-base](https://huggingface.co/readerbench/RoBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6381

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.9887        | 0.1   | 400   | 0.9251          |
| 0.9326        | 0.21  | 800   | 1.0643          |
| 0.8767        | 0.31  | 1200  | 0.8270          |
| 0.9989        | 0.41  | 1600  | 1.0447          |
| 0.8717        | 0.51  | 2000  | 0.8382          |
| 0.8298        | 0.62  | 2400  | 0.8867          |
| 0.9462        | 0.72  | 2800  | 0.8950          |
| 0.8885        | 0.82  | 3200  | 0.8633          |
| 0.9317        | 0.92  | 3600  | 0.8930          |
| 0.7629        | 1.03  | 4000  | 1.1367          |
| 0.7152        | 1.13  | 4400  | 0.9594          |
| 0.66          | 1.23  | 4800  | 0.9411          |
| 0.6867        | 1.33  | 5200  | 1.1500          |
| 0.6281        | 1.44  | 5600  | 0.9684          |
| 0.6442        | 1.54  | 6000  | 1.1268          |
| 0.6769        | 1.64  | 6400  | 0.9762          |
| 0.7184        | 1.74  | 6800  | 0.8957          |
| 0.58          | 1.85  | 7200  | 0.9875          |
| 0.5751        | 1.95  | 7600  | 1.2363          |
| 0.4031        | 2.05  | 8000  | 1.3173          |
| 0.3862        | 2.15  | 8400  | 1.3331          |
| 0.5009        | 2.26  | 8800  | 1.4265          |
| 0.4591        | 2.36  | 9200  | 1.5329          |
| 0.4284        | 2.46  | 9600  | 1.3033          |
| 0.5236        | 2.56  | 10000 | 1.2444          |
| 0.5135        | 2.67  | 10400 | 1.2472          |
| 0.5369        | 2.77  | 10800 | 1.6505          |
| 0.4701        | 2.87  | 11200 | 1.3840          |
| 0.5371        | 2.97  | 11600 | 1.3600          |
| 0.2557        | 3.08  | 12000 | 1.4148          |
| 0.2952        | 3.18  | 12400 | 1.7975          |
| 0.2098        | 3.28  | 12800 | 2.0480          |
| 0.236         | 3.38  | 13200 | 1.9231          |
| 0.2414        | 3.49  | 13600 | 1.6038          |
| 0.387         | 3.59  | 14000 | 1.6627          |
| 0.3059        | 3.69  | 14400 | 1.5931          |
| 0.2872        | 3.79  | 14800 | 1.5828          |
| 0.1751        | 3.9   | 15200 | 1.9071          |
| 0.2429        | 4.0   | 15600 | 1.6990          |
| 0.164         | 4.1   | 16000 | 1.9178          |
| 0.0941        | 4.2   | 16400 | 2.1213          |
| 0.1948        | 4.31  | 16800 | 2.0160          |
| 0.1442        | 4.41  | 17200 | 2.0305          |
| 0.2209        | 4.51  | 17600 | 1.9717          |
| 0.1375        | 4.61  | 18000 | 2.0309          |
| 0.1995        | 4.72  | 18400 | 2.0615          |
| 0.1421        | 4.82  | 18800 | 2.0320          |
| 0.2076        | 4.92  | 19200 | 1.9974          |
| 0.0748        | 5.02  | 19600 | 1.9942          |
| 0.0689        | 5.13  | 20000 | 2.1029          |
| 0.0841        | 5.23  | 20400 | 2.2356          |
| 0.0782        | 5.33  | 20800 | 2.2074          |
| 0.1662        | 5.43  | 21200 | 2.3315          |
| 0.0415        | 5.54  | 21600 | 2.5986          |
| 0.0731        | 5.64  | 22000 | 2.2913          |
| 0.0851        | 5.74  | 22400 | 2.4306          |
| 0.0923        | 5.84  | 22800 | 2.4737          |
| 0.099         | 5.95  | 23200 | 2.2077          |
| 0.0297        | 6.05  | 23600 | 2.2406          |
| 0.0365        | 6.15  | 24000 | 2.5536          |
| 0.0131        | 6.25  | 24400 | 2.7311          |
| 0.0838        | 6.36  | 24800 | 2.3021          |
| 0.0392        | 6.46  | 25200 | 2.4769          |
| 0.0357        | 6.56  | 25600 | 2.4404          |
| 0.0955        | 6.66  | 26000 | 2.4813          |
| 0.1119        | 6.77  | 26400 | 2.3819          |
| 0.0916        | 6.87  | 26800 | 2.5341          |
| 0.1437        | 6.97  | 27200 | 2.2940          |
| 0.0333        | 7.08  | 27600 | 2.4652          |
| 0.0276        | 7.18  | 28000 | 2.5684          |
| 0.0306        | 7.28  | 28400 | 2.4722          |
| 0.0248        | 7.38  | 28800 | 2.7375          |
| 0.0199        | 7.49  | 29200 | 2.7708          |
| 0.0443        | 7.59  | 29600 | 2.7067          |
| 0.0119        | 7.69  | 30000 | 2.6394          |
| 0.0606        | 7.79  | 30400 | 2.5045          |
| 0.0467        | 7.9   | 30800 | 2.3479          |
| 0.0438        | 8.0   | 31200 | 2.7489          |
| 0.0033        | 8.1   | 31600 | 2.6423          |
| 0.0306        | 8.2   | 32000 | 2.5070          |
| 0.033         | 8.31  | 32400 | 2.7068          |
| 0.0114        | 8.41  | 32800 | 2.7400          |
| 0.0032        | 8.51  | 33200 | 2.5803          |
| 0.0305        | 8.61  | 33600 | 2.8058          |
| 0.0253        | 8.72  | 34000 | 2.5497          |
| 0.0183        | 8.82  | 34400 | 2.5782          |
| 0.0651        | 8.92  | 34800 | 2.7173          |
| 0.0345        | 9.02  | 35200 | 2.5939          |
| 0.0206        | 9.13  | 35600 | 2.6243          |
| 0.0018        | 9.23  | 36000 | 2.5503          |
| 0.0484        | 9.33  | 36400 | 2.7006          |
| 0.0359        | 9.43  | 36800 | 2.6202          |
| 0.006         | 9.54  | 37200 | 2.6260          |
| 0.0205        | 9.64  | 37600 | 2.7143          |
| 0.0153        | 9.74  | 38000 | 2.6923          |
| 0.0342        | 9.84  | 38400 | 2.6475          |
| 0.011         | 9.95  | 38800 | 2.6381          |


### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "model-index": [{"name": "smashing-sexism-robert-weighted-final-2", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

smashing-sexism-robert-weighted-final-2
=======================================


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


* Loss: 2.6381


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: 10


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2



### 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: 10 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #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: 10 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #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: 10### Training results### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2