metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: convnextv2-base-22k-384-finetuned
results: []
convnextv2-base-22k-384-finetuned
This model is a fine-tuned version of facebook/convnextv2-base-22k-384 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1532
- Accuracy: 0.9611
- F1: 0.9510
- Precision: 0.9714
- Recall: 0.9315
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: 0.00015
- train_batch_size: 2
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1703 | 1.0 | 25 | 0.1399 | 0.9611 | 0.9510 | 0.9714 | 0.9315 |
| 0.0829 | 2.0 | 50 | 0.1470 | 0.9611 | 0.9510 | 0.9714 | 0.9315 |
| 0.0458 | 3.0 | 75 | 0.1532 | 0.9611 | 0.9510 | 0.9714 | 0.9315 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3