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MT-earnest-capybara-106
Browse files- README.md +47 -0
- config.json +52 -0
- preprocessor_config.json +24 -0
- pytorch_model.bin +3 -0
- training_args.bin +3 -0
README.md
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---
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base_model: toobiza/MT-smart-feather-100
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tags:
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- generated_from_trainer
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model-index:
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- name: MT-earnest-capybara-106
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results: []
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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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# MT-earnest-capybara-106
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This model is a fine-tuned version of [toobiza/MT-smart-feather-100](https://huggingface.co/toobiza/MT-smart-feather-100) on an unknown dataset.
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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: 1e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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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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- num_epochs: 3
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.13.3
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config.json
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{
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"_name_or_path": "toobiza/MT-smart-feather-100",
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"activation_dropout": 0.0,
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"activation_function": "relu",
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"architectures": [
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"TableTransformerForObjectDetection"
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],
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"attention_dropout": 0.0,
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"auxiliary_loss": false,
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"backbone": "resnet18",
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"backbone_config": null,
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"bbox_cost": 5,
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"bbox_loss_coefficient": 5,
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"ce_loss_coefficient": 1,
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"class_cost": 1,
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"d_model": 256,
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"decoder_attention_heads": 8,
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"decoder_ffn_dim": 2048,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 6,
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"dice_loss_coefficient": 1,
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"dilation": false,
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"dropout": 0.1,
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"encoder_attention_heads": 8,
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"encoder_ffn_dim": 2048,
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"encoder_layerdrop": 0.0,
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"encoder_layers": 6,
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"eos_coefficient": 0.4,
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"giou_cost": 2,
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"giou_loss_coefficient": 2,
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"id2label": {
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"1": "MainBody"
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},
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"init_std": 0.02,
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"init_xavier_std": 1.0,
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"is_encoder_decoder": true,
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"label2id": {
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"MainBody": 1
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},
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"mask_loss_coefficient": 1,
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"max_position_embeddings": 1024,
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"model_type": "table-transformer",
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"num_channels": 3,
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"num_hidden_layers": 6,
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"num_queries": 1,
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"position_embedding_type": "sine",
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"scale_embedding": false,
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"torch_dtype": "float32",
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"transformers_version": "4.33.2",
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"use_pretrained_backbone": true,
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"use_timm_backbone": true
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}
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_pad": true,
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"do_rescale": true,
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"do_resize": true,
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"format": "coco_detection",
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"image_mean": [
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0.485,
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0.456,
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0.406
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],
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"image_processor_type": "DetrImageProcessor",
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"image_std": [
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0.229,
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0.224,
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0.225
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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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"longest_edge": 800,
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"shortest_edge": 800
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}
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:5ae8c8819a2b04fa316f639ebdb1362ba99d0877558564acd273c77d74377654
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size 115385222
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:06dbc88c200892d7b76757b3ca0f094d3626921ad215d7ad362e2ce5614a4ea1
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size 4472
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