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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: canine-mouse-enhancers
  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. -->

# canine-mouse-enhancers

This model is a fine-tuned version of [google/canine-c](https://huggingface.co/google/canine-c) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9641
- Accuracy: 0.7727

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| No log        | 1.0   | 242   | 0.6476          | 0.6281   |
| No log        | 2.0   | 484   | 0.6080          | 0.6860   |
| 0.6372        | 3.0   | 726   | 0.5989          | 0.7231   |
| 0.6372        | 4.0   | 968   | 0.6285          | 0.6694   |
| 0.5955        | 5.0   | 1210  | 0.5904          | 0.6860   |
| 0.5955        | 6.0   | 1452  | 0.5782          | 0.7107   |
| 0.5812        | 7.0   | 1694  | 0.5845          | 0.6983   |
| 0.5812        | 8.0   | 1936  | 0.6186          | 0.6983   |
| 0.5901        | 9.0   | 2178  | 0.5814          | 0.7231   |
| 0.5901        | 10.0  | 2420  | 0.6152          | 0.7355   |
| 0.5535        | 11.0  | 2662  | 0.5556          | 0.7438   |
| 0.5535        | 12.0  | 2904  | 0.5476          | 0.7479   |
| 0.5566        | 13.0  | 3146  | 0.6583          | 0.7107   |
| 0.5566        | 14.0  | 3388  | 0.5571          | 0.7521   |
| 0.5419        | 15.0  | 3630  | 0.6231          | 0.7231   |
| 0.5419        | 16.0  | 3872  | 0.6068          | 0.7603   |
| 0.546         | 17.0  | 4114  | 0.6581          | 0.7273   |
| 0.546         | 18.0  | 4356  | 0.6350          | 0.7438   |
| 0.5359        | 19.0  | 4598  | 0.7081          | 0.7438   |
| 0.5359        | 20.0  | 4840  | 0.6711          | 0.7521   |
| 0.5262        | 21.0  | 5082  | 0.8095          | 0.7190   |
| 0.5262        | 22.0  | 5324  | 0.7282          | 0.7521   |
| 0.5666        | 23.0  | 5566  | 0.7604          | 0.7479   |
| 0.5666        | 24.0  | 5808  | 0.8097          | 0.7521   |
| 0.5456        | 25.0  | 6050  | 0.8513          | 0.7521   |
| 0.5456        | 26.0  | 6292  | 0.7954          | 0.7603   |
| 0.5612        | 27.0  | 6534  | 0.8435          | 0.7521   |
| 0.5612        | 28.0  | 6776  | 0.9000          | 0.7355   |
| 0.5358        | 29.0  | 7018  | 0.9241          | 0.7603   |
| 0.5358        | 30.0  | 7260  | 0.9005          | 0.7479   |
| 0.5434        | 31.0  | 7502  | 0.8875          | 0.7645   |
| 0.5434        | 32.0  | 7744  | 0.8878          | 0.7686   |
| 0.5434        | 33.0  | 7986  | 0.9162          | 0.7645   |
| 0.5066        | 34.0  | 8228  | 0.8665          | 0.7686   |
| 0.5066        | 35.0  | 8470  | 0.8756          | 0.7686   |
| 0.5276        | 36.0  | 8712  | 0.9723          | 0.7603   |
| 0.5276        | 37.0  | 8954  | 1.0044          | 0.7521   |
| 0.4916        | 38.0  | 9196  | 0.9647          | 0.7521   |
| 0.4916        | 39.0  | 9438  | 0.9819          | 0.7603   |
| 0.4865        | 40.0  | 9680  | 0.9644          | 0.7686   |
| 0.4865        | 41.0  | 9922  | 0.9084          | 0.7851   |
| 0.4505        | 42.0  | 10164 | 1.0152          | 0.7521   |
| 0.4505        | 43.0  | 10406 | 0.9332          | 0.7769   |
| 0.4798        | 44.0  | 10648 | 0.9803          | 0.7603   |
| 0.4798        | 45.0  | 10890 | 1.0211          | 0.7521   |
| 0.4234        | 46.0  | 11132 | 0.9143          | 0.7810   |
| 0.4234        | 47.0  | 11374 | 0.9969          | 0.7645   |
| 0.4269        | 48.0  | 11616 | 0.9515          | 0.7851   |
| 0.4269        | 49.0  | 11858 | 0.9998          | 0.7686   |
| 0.4135        | 50.0  | 12100 | 0.9641          | 0.7727   |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.0+cu117
- Datasets 2.19.0
- Tokenizers 0.13.3