
<!-- 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. -->

# bert_12_layer_model_v2_complete_training_new_emb_compress_48

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.8914
- Accuracy: 0.2945

## 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: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 7.111         | 0.08  | 10000  | 7.0878          | 0.0852   |
| 6.6847        | 0.16  | 20000  | 6.6790          | 0.1094   |
| 6.5375        | 0.25  | 30000  | 6.5342          | 0.1189   |
| 6.4521        | 0.33  | 40000  | 6.4410          | 0.1272   |
| 6.3795        | 0.41  | 50000  | 6.3764          | 0.1316   |
| 6.3315        | 0.49  | 60000  | 6.3245          | 0.1354   |
| 6.2877        | 0.57  | 70000  | 6.2828          | 0.1382   |
| 6.2569        | 0.66  | 80000  | 6.2511          | 0.1409   |
| 6.2242        | 0.74  | 90000  | 6.2219          | 0.1422   |
| 6.1972        | 0.82  | 100000 | 6.1979          | 0.1434   |
| 6.1799        | 0.9   | 110000 | 6.1787          | 0.1445   |
| 6.162         | 0.98  | 120000 | 6.1568          | 0.1458   |
| 6.1324        | 1.07  | 130000 | 6.1354          | 0.1469   |
| 6.1067        | 1.15  | 140000 | 6.1014          | 0.1475   |
| 6.0558        | 1.23  | 150000 | 6.0465          | 0.1493   |
| 5.9739        | 1.31  | 160000 | 5.9502          | 0.1561   |
| 5.8932        | 1.39  | 170000 | 5.8741          | 0.1683   |
| 5.7488        | 1.47  | 180000 | 5.7045          | 0.2000   |
| 5.5336        | 1.56  | 190000 | 5.4830          | 0.2298   |
| 5.3678        | 1.64  | 200000 | 5.2979          | 0.2504   |
| 5.1831        | 1.72  | 210000 | 5.1048          | 0.2714   |
| 4.9486        | 1.8   | 220000 | 4.8914          | 0.2945   |


### Framework versions

- Transformers 4.30.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "bert_12_layer_model_v2_complete_training_new_emb_compress_48", "results": []}]}
transformers pytorch tensorboard hybridbert fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #hybridbert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

bert\_12\_layer\_model\_v2\_complete\_training\_new\_emb\_compress\_48
======================================================================


This model is a fine-tuned version of [](URL on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 4.8914
* Accuracy: 0.2945


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: 1e-05
* train\_batch\_size: 48
* eval\_batch\_size: 48
* seed: 10
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10000
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.30.1
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 48
* eval\_batch\_size: 48
* seed: 10
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10000
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #hybridbert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 48
* eval\_batch\_size: 48
* seed: 10
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10000
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3