readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: dna_bert_3_2-finetuned
    results: []
  ---
  
  <!-- 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. -->
  
  # 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        