metadata
license: apache-2.0
base_model: Professor/Plant_Classification_model_vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: CGIAR
results: []
CGIAR
This model is a fine-tuned version of Professor/Plant_Classification_model_vit-base-patch16-224-in21k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 54492293329844454479773697233125376.0000
- Accuracy: 0.3544
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: 0.001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 55115298162505422799006162975981568.0000 | 1.0 | 652 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 53715036097686125832353526497411072.0000 | 2.0 | 1304 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54797447451004199141419049933602816.0000 | 3.0 | 1956 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 55388263901553770622607373979615232.0000 | 4.0 | 2608 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 53851460655282681977584498109317120.0000 | 5.0 | 3260 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54308925333290649361019457834582016.0000 | 6.0 | 3912 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 53835980106152695430429230728478720.0000 | 7.0 | 4564 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54913731575864339655669675792007168.0000 | 8.0 | 5216 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54491948726951597801593618575654912.0000 | 9.0 | 5868 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54398877819882843412545019471462400.0000 | 10.0 | 6520 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 55282800442217187571686937129385984.0000 | 11.0 | 7172 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 52815607573209785396379970885910528.0000 | 12.0 | 7824 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54668735279659425567121704382103552.0000 | 13.0 | 8476 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54364772948134300251035076669734912.0000 | 14.0 | 9128 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 55368087974600541370080109424279552.0000 | 15.0 | 9780 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 53516527084292779675316787406176256.0000 | 16.0 | 10432 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 55183553541424117412071478755590144.0000 | 17.0 | 11084 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54012776800065327087827864764022784.0000 | 18.0 | 11736 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 55169594173014401050849192676687872.0000 | 19.0 | 12388 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54620650757091567484020415898058752.0000 | 20.0 | 13040 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54960264494097515877226338286829568.0000 | 21.0 | 13692 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 55368087974600541370080109424279552.0000 | 22.0 | 14344 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 52922607425073853694411248236494848.0000 | 23.0 | 14996 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54944718027136313256284544271646720.0000 | 24.0 | 15648 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54712129495006442890786269806198784.0000 | 25.0 | 16300 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54367876156803663974124328648179712.0000 | 26.0 | 16952 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54160082870414245600868241049124864.0000 | 27.0 | 17604 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 55163397896880486719913273803669504.0000 | 28.0 | 18256 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54122849436984347433336749405765632.0000 | 29.0 | 18908 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54177145447493325685179779106471936.0000 | 30.0 | 19560 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54541549359637333348064651101863936.0000 | 31.0 | 20212 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54251576820136317622067880446132224.0000 | 32.0 | 20864 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 53716587702020798470526115631857664.0000 | 33.0 | 21516 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 55282835936433991969861819076444160.0000 | 34.0 | 22168 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 53339720249175353349419641996312576.0000 | 35.0 | 22820 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54564793001043112702134248833810432.0000 | 36.0 | 23472 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 55064145925485014614362541315325952.0000 | 37.0 | 24124 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 53395588146428612023176357289656320.0000 | 38.0 | 24776 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 55016101967736372098743445747662848.0000 | 39.0 | 25428 | 54492293329844454479773697233125376.0000 | 0.3544 |
| 54552410589980087932132959316869120.0000 | 40.0 | 26080 | 54492293329844454479773697233125376.0000 | 0.3544 |
Framework versions
- Transformers 4.36.1
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0