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---
license: apache-2.0
base_model: google/canine-c
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: canine_deasciifier_final_0701_v8
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_deasciifier_final_0701_v8
This model is a fine-tuned version of [google/canine-c](https://huggingface.co/google/canine-c) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0340
- Precision: 0.9153
- Recall: 0.9338
- F1: 0.9244
- Accuracy: 0.9918
## 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 488 | 0.0903 | 0.6868 | 0.7578 | 0.7205 | 0.9660 |
| 0.2413 | 2.0 | 976 | 0.0562 | 0.8068 | 0.8466 | 0.8262 | 0.9800 |
| 0.0812 | 3.0 | 1464 | 0.0409 | 0.8669 | 0.8674 | 0.8672 | 0.9854 |
| 0.052 | 4.0 | 1952 | 0.0381 | 0.8664 | 0.8971 | 0.8815 | 0.9870 |
| 0.0377 | 5.0 | 2440 | 0.0370 | 0.8738 | 0.9038 | 0.8886 | 0.9877 |
| 0.0291 | 6.0 | 2928 | 0.0314 | 0.9071 | 0.9088 | 0.9079 | 0.9900 |
| 0.0234 | 7.0 | 3416 | 0.0340 | 0.8867 | 0.9191 | 0.9026 | 0.9892 |
| 0.0196 | 8.0 | 3904 | 0.0325 | 0.9030 | 0.9242 | 0.9135 | 0.9905 |
| 0.0158 | 9.0 | 4392 | 0.0319 | 0.9109 | 0.9266 | 0.9187 | 0.9911 |
| 0.0132 | 10.0 | 4880 | 0.0329 | 0.9087 | 0.9318 | 0.9201 | 0.9913 |
| 0.0113 | 11.0 | 5368 | 0.0331 | 0.9045 | 0.9315 | 0.9178 | 0.9910 |
| 0.0099 | 12.0 | 5856 | 0.0337 | 0.9088 | 0.9314 | 0.9200 | 0.9913 |
| 0.0083 | 13.0 | 6344 | 0.0346 | 0.9133 | 0.9357 | 0.9244 | 0.9917 |
| 0.0081 | 14.0 | 6832 | 0.0332 | 0.9167 | 0.9324 | 0.9245 | 0.9918 |
| 0.0071 | 15.0 | 7320 | 0.0340 | 0.9153 | 0.9338 | 0.9244 | 0.9918 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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