End of training
Browse files
README.md
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: Chess-model
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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config: default
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split: train[:258]
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.6346153846153846
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Chess-model
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7148
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- Accuracy: 0.6346
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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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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| No log | 0.92 | 3 | 1.0361 | 0.5192 |
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| No log | 1.85 | 6 | 0.9621 | 0.5962 |
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| No log | 2.77 | 9 | 0.8925 | 0.6154 |
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| 0.9964 | 4.0 | 13 | 0.8220 | 0.5962 |
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| 0.9964 | 4.92 | 16 | 0.8058 | 0.5769 |
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| 0.9964 | 5.85 | 19 | 0.7298 | 0.6346 |
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| 0.7724 | 6.77 | 22 | 0.7314 | 0.6346 |
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| 0.7724 | 8.0 | 26 | 0.7068 | 0.6538 |
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| 0.7724 | 8.92 | 29 | 0.6655 | 0.6731 |
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| 0.6697 | 9.23 | 30 | 0.7148 | 0.6346 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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config.json
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{
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"_name_or_path": "google/vit-base-patch16-224-in21k",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "King",
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"1": "Knight",
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"2": "Queen"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"King": 0,
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"Knight": 1,
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"Queen": 2
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"num_attention_heads": 12,
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.38.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:384499a998f91b8c7f2c4df70dcba09ccf7a93e683b864550718d8eca9637687
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size 343227052
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "ViTImageProcessor",
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"image_std": [
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0.5,
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0.5,
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0.5
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],
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 224,
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"width": 224
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}
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}
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runs/Apr03_08-33-18_f6b82baa01c4/events.out.tfevents.1712133206.f6b82baa01c4.910.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:903aacbd30566d2c1881fc1d1299e35432b1e6da795f7b60afb7804046868836
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size 8712
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runs/Apr03_08-38-57_f6b82baa01c4/events.out.tfevents.1712133543.f6b82baa01c4.6711.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:e1bb3edbf496134cf3a3df4712a4b6eda34ac96e9c1830ef908f6e658bf96192
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:65042c07e8021d7e845275ec47e8368488416fa6c21c95a4976d4c55ce635718
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size 4920
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