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tigeryi
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imagenet-tiger

Image Classification
Transformers
TensorBoard
Safetensors
data2vec-vision
Generated from Trainer
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@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [tigeryi/imagenet1k](https://huggingface.co/tigeryi/imagenet1k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 6.4890
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- - Accuracy: 0.0105
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.001
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  - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 1
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  - optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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- - num_epochs: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 6.9338 | 0.4 | 1000 | 6.7408 | 0.0056 |
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- | 6.7129 | 0.8 | 2000 | 6.4890 | 0.0105 |
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  ### Framework versions
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- - Transformers 4.40.0
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.19.0
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  - Tokenizers 0.19.1
 
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  This model is a fine-tuned version of [tigeryi/imagenet1k](https://huggingface.co/tigeryi/imagenet1k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0970
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+ - Accuracy: 0.99
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 1
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  - optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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+ - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.8141 | 1.0 | 25 | 0.2320 | 0.95 |
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+ | 0.7293 | 2.0 | 50 | 0.0970 | 0.99 |
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  ### Framework versions
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+ - Transformers 4.40.1
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.19.0
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  - Tokenizers 0.19.1