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# dna_bert_3_2-finetuned

This model is a fine-tuned version of [armheb/DNA_bert_3](https://huggingface.co/armheb/DNA_bert_3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4668

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8974        | 1.0   | 62   | 0.6160          |
| 0.6057        | 2.0   | 124  | 0.6000          |
| 0.5957        | 3.0   | 186  | 0.5897          |
| 0.5883        | 4.0   | 248  | 0.5873          |
| 0.5844        | 5.0   | 310  | 0.5843          |
| 0.5812        | 6.0   | 372  | 0.5811          |
| 0.5812        | 7.0   | 434  | 0.5832          |
| 0.5769        | 8.0   | 496  | 0.5773          |
| 0.5727        | 9.0   | 558  | 0.5771          |
| 0.5702        | 10.0  | 620  | 0.5772          |
| 0.5673        | 11.0  | 682  | 0.5771          |
| 0.5663        | 12.0  | 744  | 0.5769          |
| 0.5569        | 13.0  | 806  | 0.5731          |
| 0.5518        | 14.0  | 868  | 0.5731          |
| 0.5486        | 15.0  | 930  | 0.5728          |
| 0.544         | 16.0  | 992  | 0.5683          |
| 0.5336        | 17.0  | 1054 | 0.5694          |
| 0.5245        | 18.0  | 1116 | 0.5639          |
| 0.5162        | 19.0  | 1178 | 0.5641          |
| 0.5057        | 20.0  | 1240 | 0.5626          |
| 0.4966        | 21.0  | 1302 | 0.5612          |
| 0.4859        | 22.0  | 1364 | 0.5492          |
| 0.4781        | 23.0  | 1426 | 0.5470          |
| 0.4601        | 24.0  | 1488 | 0.5399          |
| 0.4523        | 25.0  | 1550 | 0.5424          |
| 0.4432        | 26.0  | 1612 | 0.5328          |
| 0.4341        | 27.0  | 1674 | 0.5336          |
| 0.4183        | 28.0  | 1736 | 0.5315          |
| 0.4133        | 29.0  | 1798 | 0.5268          |
| 0.4111        | 30.0  | 1860 | 0.5256          |
| 0.3919        | 31.0  | 1922 | 0.5155          |
| 0.3899        | 32.0  | 1984 | 0.5179          |
| 0.3804        | 33.0  | 2046 | 0.5145          |
| 0.368         | 34.0  | 2108 | 0.5189          |
| 0.3603        | 35.0  | 2170 | 0.5081          |
| 0.3602        | 36.0  | 2232 | 0.5098          |
| 0.352         | 37.0  | 2294 | 0.5054          |
| 0.3468        | 38.0  | 2356 | 0.5024          |
| 0.3359        | 39.0  | 2418 | 0.5053          |
| 0.3342        | 40.0  | 2480 | 0.5031          |
| 0.3294        | 41.0  | 2542 | 0.4978          |
| 0.3158        | 42.0  | 2604 | 0.4923          |
| 0.3191        | 43.0  | 2666 | 0.4944          |
| 0.3122        | 44.0  | 2728 | 0.4970          |
| 0.3084        | 45.0  | 2790 | 0.4910          |
| 0.2978        | 46.0  | 2852 | 0.4898          |
| 0.3012        | 47.0  | 2914 | 0.4880          |
| 0.2938        | 48.0  | 2976 | 0.4924          |
| 0.2932        | 49.0  | 3038 | 0.4879          |
| 0.2842        | 50.0  | 3100 | 0.4847          |
| 0.2828        | 51.0  | 3162 | 0.4849          |
| 0.2793        | 52.0  | 3224 | 0.4767          |
| 0.2753        | 53.0  | 3286 | 0.4796          |
| 0.2725        | 54.0  | 3348 | 0.4829          |
| 0.2695        | 55.0  | 3410 | 0.4831          |
| 0.2671        | 56.0  | 3472 | 0.4791          |
| 0.2664        | 57.0  | 3534 | 0.4791          |
| 0.2563        | 58.0  | 3596 | 0.4765          |
| 0.2583        | 59.0  | 3658 | 0.4742          |
| 0.2535        | 60.0  | 3720 | 0.4766          |
| 0.2496        | 61.0  | 3782 | 0.4741          |
| 0.2489        | 62.0  | 3844 | 0.4766          |
| 0.2444        | 63.0  | 3906 | 0.4748          |
| 0.2417        | 64.0  | 3968 | 0.4768          |
| 0.2422        | 65.0  | 4030 | 0.4727          |
| 0.2404        | 66.0  | 4092 | 0.4729          |
| 0.2405        | 67.0  | 4154 | 0.4744          |
| 0.2353        | 68.0  | 4216 | 0.4729          |
| 0.2307        | 69.0  | 4278 | 0.4705          |
| 0.2281        | 70.0  | 4340 | 0.4717          |
| 0.232         | 71.0  | 4402 | 0.4719          |
| 0.2313        | 72.0  | 4464 | 0.4713          |
| 0.2266        | 73.0  | 4526 | 0.4726          |
| 0.2241        | 74.0  | 4588 | 0.4675          |
| 0.2256        | 75.0  | 4650 | 0.4688          |
| 0.2299        | 76.0  | 4712 | 0.4713          |
| 0.2199        | 77.0  | 4774 | 0.4720          |
| 0.2228        | 78.0  | 4836 | 0.4682          |
| 0.2261        | 79.0  | 4898 | 0.4676          |
| 0.2167        | 80.0  | 4960 | 0.4685          |
| 0.2126        | 81.0  | 5022 | 0.4676          |
| 0.2217        | 82.0  | 5084 | 0.4672          |
| 0.216         | 83.0  | 5146 | 0.4672          |
| 0.2152        | 84.0  | 5208 | 0.4682          |
| 0.219         | 85.0  | 5270 | 0.4663          |
| 0.2135        | 86.0  | 5332 | 0.4655          |
| 0.2046        | 87.0  | 5394 | 0.4644          |
| 0.2177        | 88.0  | 5456 | 0.4679          |
| 0.2052        | 89.0  | 5518 | 0.4659          |
| 0.2147        | 90.0  | 5580 | 0.4665          |
| 0.211         | 91.0  | 5642 | 0.4668          |
| 0.2089        | 92.0  | 5704 | 0.4649          |
| 0.2149        | 93.0  | 5766 | 0.4651          |
| 0.2034        | 94.0  | 5828 | 0.4689          |
| 0.2071        | 95.0  | 5890 | 0.4659          |
| 0.2145        | 96.0  | 5952 | 0.4664          |
| 0.2036        | 97.0  | 6014 | 0.4661          |
| 0.2092        | 98.0  | 6076 | 0.4676          |
| 0.2079        | 99.0  | 6138 | 0.4667          |
| 0.2081        | 100.0 | 6200 | 0.4668          |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "dna_bert_3_2-finetuned", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

dna\_bert\_3\_2-finetuned
=========================


This model is a fine-tuned version of armheb/DNA\_bert\_3 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4668


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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.21.1
* 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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1