update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,85 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- generated_from_trainer
|
| 4 |
+
model-index:
|
| 5 |
+
- name: DNADebertaK6_Zebrafish
|
| 6 |
+
results: []
|
| 7 |
+
---
|
| 8 |
+
|
| 9 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 10 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 11 |
+
|
| 12 |
+
# DNADebertaK6_Zebrafish
|
| 13 |
+
|
| 14 |
+
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
|
| 15 |
+
It achieves the following results on the evaluation set:
|
| 16 |
+
- Loss: 1.4958
|
| 17 |
+
|
| 18 |
+
## Model description
|
| 19 |
+
|
| 20 |
+
More information needed
|
| 21 |
+
|
| 22 |
+
## Intended uses & limitations
|
| 23 |
+
|
| 24 |
+
More information needed
|
| 25 |
+
|
| 26 |
+
## Training and evaluation data
|
| 27 |
+
|
| 28 |
+
More information needed
|
| 29 |
+
|
| 30 |
+
## Training procedure
|
| 31 |
+
|
| 32 |
+
### Training hyperparameters
|
| 33 |
+
|
| 34 |
+
The following hyperparameters were used during training:
|
| 35 |
+
- learning_rate: 5e-05
|
| 36 |
+
- train_batch_size: 64
|
| 37 |
+
- eval_batch_size: 64
|
| 38 |
+
- seed: 42
|
| 39 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 40 |
+
- lr_scheduler_type: linear
|
| 41 |
+
- training_steps: 600001
|
| 42 |
+
- mixed_precision_training: Native AMP
|
| 43 |
+
|
| 44 |
+
### Training results
|
| 45 |
+
|
| 46 |
+
| Training Loss | Epoch | Step | Validation Loss |
|
| 47 |
+
|:-------------:|:-----:|:------:|:---------------:|
|
| 48 |
+
| 4.1727 | 0.59 | 20000 | 1.8535 |
|
| 49 |
+
| 1.8381 | 1.18 | 40000 | 1.7512 |
|
| 50 |
+
| 1.7561 | 1.77 | 60000 | 1.7235 |
|
| 51 |
+
| 1.7281 | 2.36 | 80000 | 1.7019 |
|
| 52 |
+
| 1.7065 | 2.95 | 100000 | 1.6822 |
|
| 53 |
+
| 1.6876 | 3.54 | 120000 | 1.6639 |
|
| 54 |
+
| 1.6718 | 4.13 | 140000 | 1.6501 |
|
| 55 |
+
| 1.6562 | 4.71 | 160000 | 1.6350 |
|
| 56 |
+
| 1.6429 | 5.3 | 180000 | 1.6211 |
|
| 57 |
+
| 1.6313 | 5.89 | 200000 | 1.6102 |
|
| 58 |
+
| 1.6207 | 6.48 | 220000 | 1.6001 |
|
| 59 |
+
| 1.6099 | 7.07 | 240000 | 1.5902 |
|
| 60 |
+
| 1.6 | 7.66 | 260000 | 1.5799 |
|
| 61 |
+
| 1.5925 | 8.25 | 280000 | 1.5726 |
|
| 62 |
+
| 1.5847 | 8.84 | 300000 | 1.5645 |
|
| 63 |
+
| 1.5783 | 9.43 | 320000 | 1.5596 |
|
| 64 |
+
| 1.5712 | 10.02 | 340000 | 1.5510 |
|
| 65 |
+
| 1.5656 | 10.61 | 360000 | 1.5452 |
|
| 66 |
+
| 1.5598 | 11.2 | 380000 | 1.5410 |
|
| 67 |
+
| 1.5548 | 11.79 | 400000 | 1.5342 |
|
| 68 |
+
| 1.5497 | 12.38 | 420000 | 1.5293 |
|
| 69 |
+
| 1.546 | 12.96 | 440000 | 1.5241 |
|
| 70 |
+
| 1.5397 | 13.55 | 460000 | 1.5214 |
|
| 71 |
+
| 1.5365 | 14.14 | 480000 | 1.5164 |
|
| 72 |
+
| 1.5321 | 14.73 | 500000 | 1.5115 |
|
| 73 |
+
| 1.5285 | 15.32 | 520000 | 1.5075 |
|
| 74 |
+
| 1.5246 | 15.91 | 540000 | 1.5034 |
|
| 75 |
+
| 1.5217 | 16.5 | 560000 | 1.5029 |
|
| 76 |
+
| 1.5191 | 17.09 | 580000 | 1.4995 |
|
| 77 |
+
| 1.516 | 17.68 | 600000 | 1.4958 |
|
| 78 |
+
|
| 79 |
+
|
| 80 |
+
### Framework versions
|
| 81 |
+
|
| 82 |
+
- Transformers 4.19.2
|
| 83 |
+
- Pytorch 1.11.0
|
| 84 |
+
- Datasets 2.2.2
|
| 85 |
+
- Tokenizers 0.12.1
|