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# trainer_log

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4907
- Accuracy: 0.8742

## 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: 64
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.047         | 0.04  | 5    | 0.9927          | 0.5753   |
| 0.938         | 0.08  | 10   | 0.9320          | 0.5753   |
| 0.8959        | 0.12  | 15   | 0.8764          | 0.5773   |
| 0.8764        | 0.16  | 20   | 0.8308          | 0.6639   |
| 0.7968        | 0.2   | 25   | 0.8045          | 0.6577   |
| 0.8644        | 0.25  | 30   | 0.7779          | 0.6639   |
| 0.7454        | 0.29  | 35   | 0.7561          | 0.6412   |
| 0.7008        | 0.33  | 40   | 0.7157          | 0.6845   |
| 0.7627        | 0.37  | 45   | 0.7027          | 0.6907   |
| 0.7568        | 0.41  | 50   | 0.7270          | 0.6763   |
| 0.7042        | 0.45  | 55   | 0.6770          | 0.7031   |
| 0.6683        | 0.49  | 60   | 0.6364          | 0.7134   |
| 0.6312        | 0.53  | 65   | 0.6151          | 0.7278   |
| 0.5789        | 0.57  | 70   | 0.6003          | 0.7443   |
| 0.5964        | 0.61  | 75   | 0.5665          | 0.7835   |
| 0.5178        | 0.66  | 80   | 0.5506          | 0.8      |
| 0.5698        | 0.7   | 85   | 0.5240          | 0.8      |
| 0.5407        | 0.74  | 90   | 0.5223          | 0.7814   |
| 0.6141        | 0.78  | 95   | 0.4689          | 0.8268   |
| 0.4998        | 0.82  | 100  | 0.4491          | 0.8227   |
| 0.4853        | 0.86  | 105  | 0.4448          | 0.8268   |
| 0.4561        | 0.9   | 110  | 0.4646          | 0.8309   |
| 0.5058        | 0.94  | 115  | 0.4317          | 0.8495   |
| 0.4229        | 0.98  | 120  | 0.4014          | 0.8515   |
| 0.2808        | 1.02  | 125  | 0.3834          | 0.8619   |
| 0.3721        | 1.07  | 130  | 0.3829          | 0.8619   |
| 0.3432        | 1.11  | 135  | 0.4212          | 0.8598   |
| 0.3616        | 1.15  | 140  | 0.3930          | 0.8680   |
| 0.3912        | 1.19  | 145  | 0.3793          | 0.8639   |
| 0.4141        | 1.23  | 150  | 0.3646          | 0.8619   |
| 0.2726        | 1.27  | 155  | 0.3609          | 0.8701   |
| 0.2021        | 1.31  | 160  | 0.3640          | 0.8680   |
| 0.3468        | 1.35  | 165  | 0.3655          | 0.8701   |
| 0.2729        | 1.39  | 170  | 0.4054          | 0.8495   |
| 0.3885        | 1.43  | 175  | 0.3559          | 0.8639   |
| 0.446         | 1.48  | 180  | 0.3390          | 0.8680   |
| 0.3337        | 1.52  | 185  | 0.3505          | 0.8660   |
| 0.3507        | 1.56  | 190  | 0.3337          | 0.8804   |
| 0.3864        | 1.6   | 195  | 0.3476          | 0.8660   |
| 0.3495        | 1.64  | 200  | 0.3574          | 0.8577   |
| 0.3388        | 1.68  | 205  | 0.3426          | 0.8701   |
| 0.358         | 1.72  | 210  | 0.3439          | 0.8804   |
| 0.1761        | 1.76  | 215  | 0.3461          | 0.8722   |
| 0.3089        | 1.8   | 220  | 0.3638          | 0.8639   |
| 0.279         | 1.84  | 225  | 0.3527          | 0.8742   |
| 0.3468        | 1.89  | 230  | 0.3497          | 0.8619   |
| 0.2969        | 1.93  | 235  | 0.3572          | 0.8598   |
| 0.2719        | 1.97  | 240  | 0.3391          | 0.8804   |
| 0.1936        | 2.01  | 245  | 0.3415          | 0.8619   |
| 0.2475        | 2.05  | 250  | 0.3477          | 0.8784   |
| 0.1759        | 2.09  | 255  | 0.3718          | 0.8660   |
| 0.2443        | 2.13  | 260  | 0.3758          | 0.8619   |
| 0.2189        | 2.17  | 265  | 0.3670          | 0.8639   |
| 0.1505        | 2.21  | 270  | 0.3758          | 0.8722   |
| 0.2283        | 2.25  | 275  | 0.3723          | 0.8722   |
| 0.155         | 2.3   | 280  | 0.4442          | 0.8330   |
| 0.317         | 2.34  | 285  | 0.3700          | 0.8701   |
| 0.1566        | 2.38  | 290  | 0.4218          | 0.8619   |
| 0.2294        | 2.42  | 295  | 0.3820          | 0.8660   |
| 0.1567        | 2.46  | 300  | 0.3891          | 0.8660   |
| 0.1875        | 2.5   | 305  | 0.3973          | 0.8722   |
| 0.2741        | 2.54  | 310  | 0.4042          | 0.8742   |
| 0.2363        | 2.58  | 315  | 0.3777          | 0.8660   |
| 0.1964        | 2.62  | 320  | 0.3891          | 0.8639   |
| 0.156         | 2.66  | 325  | 0.3998          | 0.8639   |
| 0.1422        | 2.7   | 330  | 0.4022          | 0.8722   |
| 0.2141        | 2.75  | 335  | 0.4239          | 0.8701   |
| 0.1616        | 2.79  | 340  | 0.4094          | 0.8722   |
| 0.1032        | 2.83  | 345  | 0.4263          | 0.8784   |
| 0.2313        | 2.87  | 350  | 0.4579          | 0.8598   |
| 0.0843        | 2.91  | 355  | 0.3989          | 0.8742   |
| 0.2567        | 2.95  | 360  | 0.4051          | 0.8660   |
| 0.1749        | 2.99  | 365  | 0.4136          | 0.8660   |
| 0.1116        | 3.03  | 370  | 0.4312          | 0.8619   |
| 0.1058        | 3.07  | 375  | 0.4007          | 0.8701   |
| 0.1085        | 3.11  | 380  | 0.4174          | 0.8660   |
| 0.0578        | 3.16  | 385  | 0.4163          | 0.8763   |
| 0.1381        | 3.2   | 390  | 0.4578          | 0.8660   |
| 0.1137        | 3.24  | 395  | 0.4259          | 0.8660   |
| 0.2068        | 3.28  | 400  | 0.3976          | 0.8701   |
| 0.0792        | 3.32  | 405  | 0.3824          | 0.8763   |
| 0.1711        | 3.36  | 410  | 0.3793          | 0.8742   |
| 0.0686        | 3.4   | 415  | 0.4013          | 0.8742   |
| 0.1102        | 3.44  | 420  | 0.4113          | 0.8639   |
| 0.1102        | 3.48  | 425  | 0.4276          | 0.8619   |
| 0.0674        | 3.52  | 430  | 0.4222          | 0.8804   |
| 0.0453        | 3.57  | 435  | 0.4326          | 0.8722   |
| 0.0704        | 3.61  | 440  | 0.4684          | 0.8722   |
| 0.1151        | 3.65  | 445  | 0.4640          | 0.8701   |
| 0.1225        | 3.69  | 450  | 0.4408          | 0.8763   |
| 0.0391        | 3.73  | 455  | 0.4520          | 0.8639   |
| 0.0566        | 3.77  | 460  | 0.4558          | 0.8680   |
| 0.1222        | 3.81  | 465  | 0.4599          | 0.8660   |
| 0.1035        | 3.85  | 470  | 0.4630          | 0.8763   |
| 0.1845        | 3.89  | 475  | 0.4796          | 0.8680   |
| 0.087         | 3.93  | 480  | 0.4697          | 0.8742   |
| 0.1599        | 3.98  | 485  | 0.4663          | 0.8784   |
| 0.0632        | 4.02  | 490  | 0.5139          | 0.8536   |
| 0.1218        | 4.06  | 495  | 0.4920          | 0.8722   |
| 0.0916        | 4.1   | 500  | 0.4846          | 0.8763   |
| 0.0208        | 4.14  | 505  | 0.5269          | 0.8722   |
| 0.0803        | 4.18  | 510  | 0.5154          | 0.8784   |
| 0.1318        | 4.22  | 515  | 0.4907          | 0.8742   |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "trainer_log", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

trainer\_log
============


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


* Loss: 0.4907
* Accuracy: 0.8742


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: 64
* 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 4.21.1
* Pytorch 1.12.1+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: 32
* eval\_batch\_size: 64
* 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 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #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: 32
* eval\_batch\_size: 64
* 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 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #text-classification #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: 32
* eval\_batch\_size: 64
* 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 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1