metadata

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: []

canine_deasciifier_final_0701_v8

This model is a fine-tuned version of 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