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Fer_vit_jaffe_GOOGLE_1

Image Classification
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Generated from Trainer
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End of training

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  1. README.md +178 -0
  2. model.safetensors +1 -1
  3. runs/Apr24_17-59-25_6831071e4a3b/events.out.tfevents.1745517566.6831071e4a3b.30.1 +2 -2
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: WinKawaks/vit-tiny-patch16-224
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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: Fer_vit_jaffe_GOOGLE_1
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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: validation
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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: 0.8333333333333334
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+ ---
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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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+
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+ # Fer_vit_jaffe_GOOGLE_1
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+
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+ This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4137
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+ - Accuracy: 0.8333
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - eval_batch_size: 32
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+ - seed: 1
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 1 | 2.4981 | 0.1333 |
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+ | No log | 2.0 | 2 | 2.4022 | 0.1333 |
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+ | No log | 3.0 | 3 | 2.2167 | 0.1 |
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+ | No log | 4.0 | 4 | 2.0743 | 0.1333 |
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+ | No log | 5.0 | 5 | 1.9393 | 0.1 |
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+ | No log | 6.0 | 6 | 2.0201 | 0.1667 |
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+ | No log | 7.0 | 7 | 1.9793 | 0.1667 |
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+ | No log | 8.0 | 8 | 1.9287 | 0.2 |
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+ | No log | 9.0 | 9 | 1.8316 | 0.1667 |
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+ | 2.1031 | 10.0 | 10 | 1.6923 | 0.4667 |
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+ | 2.1031 | 11.0 | 11 | 1.7380 | 0.2667 |
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+ | 2.1031 | 12.0 | 12 | 1.7164 | 0.3333 |
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+ | 2.1031 | 13.0 | 13 | 1.6525 | 0.3333 |
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+ | 2.1031 | 14.0 | 14 | 1.5759 | 0.3333 |
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+ | 2.1031 | 15.0 | 15 | 1.5251 | 0.3333 |
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+ | 2.1031 | 16.0 | 16 | 1.4557 | 0.4333 |
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+ | 2.1031 | 17.0 | 17 | 1.3619 | 0.4333 |
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+ | 2.1031 | 18.0 | 18 | 1.2880 | 0.4333 |
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+ | 2.1031 | 19.0 | 19 | 1.2356 | 0.5667 |
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+ | 1.2981 | 20.0 | 20 | 1.1369 | 0.6 |
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+ | 1.2981 | 21.0 | 21 | 1.1489 | 0.5 |
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+ | 1.2981 | 22.0 | 22 | 1.0756 | 0.7 |
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+ | 1.2981 | 23.0 | 23 | 1.0136 | 0.5333 |
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+ | 1.2981 | 24.0 | 24 | 1.0509 | 0.5333 |
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+ | 1.2981 | 25.0 | 25 | 0.9975 | 0.6 |
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+ | 1.2981 | 26.0 | 26 | 0.9895 | 0.6 |
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+ | 1.2981 | 27.0 | 27 | 0.9735 | 0.6 |
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+ | 1.2981 | 28.0 | 28 | 0.9328 | 0.6 |
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+ | 1.2981 | 29.0 | 29 | 0.9559 | 0.6667 |
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+ | 0.5735 | 30.0 | 30 | 0.8359 | 0.7667 |
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+ | 0.5735 | 31.0 | 31 | 0.8023 | 0.7667 |
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+ | 0.5735 | 32.0 | 32 | 0.8285 | 0.6333 |
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+ | 0.5735 | 33.0 | 33 | 0.7287 | 0.7 |
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+ | 0.5735 | 34.0 | 34 | 0.7043 | 0.7667 |
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+ | 0.5735 | 35.0 | 35 | 0.8992 | 0.7333 |
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+ | 0.5735 | 36.0 | 36 | 0.8664 | 0.7667 |
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+ | 0.5735 | 37.0 | 37 | 0.8023 | 0.7333 |
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+ | 0.5735 | 38.0 | 38 | 0.6910 | 0.7667 |
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+ | 0.5735 | 39.0 | 39 | 0.8197 | 0.6667 |
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+ | 0.2477 | 40.0 | 40 | 0.5915 | 0.7667 |
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+ | 0.2477 | 41.0 | 41 | 0.9184 | 0.6333 |
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+ | 0.2477 | 42.0 | 42 | 0.6734 | 0.7 |
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+ | 0.2477 | 43.0 | 43 | 0.9225 | 0.7 |
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+ | 0.2477 | 44.0 | 44 | 0.5961 | 0.8 |
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+ | 0.2477 | 45.0 | 45 | 0.7012 | 0.7 |
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+ | 0.2477 | 46.0 | 46 | 0.9223 | 0.6 |
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+ | 0.2477 | 47.0 | 47 | 0.5819 | 0.7 |
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+ | 0.2477 | 48.0 | 48 | 0.7171 | 0.7333 |
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+ | 0.2477 | 49.0 | 49 | 0.6416 | 0.7667 |
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+ | 0.1117 | 50.0 | 50 | 0.8718 | 0.7 |
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+ | 0.1117 | 51.0 | 51 | 0.4941 | 0.8 |
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+ | 0.1117 | 52.0 | 52 | 0.7385 | 0.8 |
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+ | 0.1117 | 53.0 | 53 | 0.6660 | 0.8333 |
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+ | 0.1117 | 54.0 | 54 | 0.6988 | 0.8667 |
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+ | 0.1117 | 55.0 | 55 | 0.7074 | 0.7667 |
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+ | 0.1117 | 56.0 | 56 | 0.5847 | 0.8 |
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+ | 0.1117 | 57.0 | 57 | 0.6636 | 0.8 |
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+ | 0.1117 | 58.0 | 58 | 0.5520 | 0.8333 |
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+ | 0.1117 | 59.0 | 59 | 0.6299 | 0.7667 |
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+ | 0.0591 | 60.0 | 60 | 0.6717 | 0.7667 |
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+ | 0.0591 | 61.0 | 61 | 0.4874 | 0.8333 |
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+ | 0.0591 | 62.0 | 62 | 0.4603 | 0.8 |
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+ | 0.0591 | 63.0 | 63 | 0.5516 | 0.7333 |
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+ | 0.0591 | 64.0 | 64 | 0.4729 | 0.8 |
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+ | 0.0591 | 65.0 | 65 | 0.5710 | 0.7667 |
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+ | 0.0591 | 66.0 | 66 | 0.8985 | 0.7 |
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+ | 0.0591 | 67.0 | 67 | 0.8074 | 0.7667 |
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+ | 0.0591 | 68.0 | 68 | 0.5652 | 0.8 |
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+ | 0.0591 | 69.0 | 69 | 0.5538 | 0.8333 |
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+ | 0.0296 | 70.0 | 70 | 0.5727 | 0.7333 |
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+ | 0.0296 | 71.0 | 71 | 0.6359 | 0.8 |
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+ | 0.0296 | 72.0 | 72 | 0.6932 | 0.7333 |
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+ | 0.0296 | 73.0 | 73 | 0.9025 | 0.6667 |
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+ | 0.0296 | 74.0 | 74 | 0.6639 | 0.7333 |
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+ | 0.0296 | 75.0 | 75 | 0.8385 | 0.7333 |
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+ | 0.0296 | 76.0 | 76 | 0.5827 | 0.8 |
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+ | 0.0296 | 77.0 | 77 | 0.5443 | 0.8667 |
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+ | 0.0296 | 78.0 | 78 | 0.6330 | 0.8333 |
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+ | 0.0296 | 79.0 | 79 | 0.6706 | 0.7333 |
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+ | 0.0175 | 80.0 | 80 | 0.7803 | 0.8 |
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+ | 0.0175 | 81.0 | 81 | 0.5401 | 0.8 |
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+ | 0.0175 | 82.0 | 82 | 0.6806 | 0.8333 |
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+ | 0.0175 | 83.0 | 83 | 0.3827 | 0.8 |
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+ | 0.0175 | 84.0 | 84 | 0.7853 | 0.8 |
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+ | 0.0175 | 85.0 | 85 | 0.4391 | 0.8333 |
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+ | 0.0175 | 86.0 | 86 | 0.6061 | 0.8 |
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+ | 0.0175 | 87.0 | 87 | 0.4797 | 0.8 |
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+ | 0.0175 | 88.0 | 88 | 0.4386 | 0.8333 |
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+ | 0.0175 | 89.0 | 89 | 0.6556 | 0.8 |
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+ | 0.0121 | 90.0 | 90 | 0.7927 | 0.8 |
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+ | 0.0121 | 91.0 | 91 | 0.4925 | 0.8333 |
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+ | 0.0121 | 92.0 | 92 | 0.6280 | 0.7667 |
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+ | 0.0121 | 93.0 | 93 | 0.3561 | 0.9 |
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+ | 0.0121 | 94.0 | 94 | 0.6058 | 0.8333 |
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+ | 0.0121 | 95.0 | 95 | 0.5086 | 0.8 |
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+ | 0.0121 | 96.0 | 96 | 0.3854 | 0.8667 |
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+ | 0.0121 | 97.0 | 97 | 0.8370 | 0.7667 |
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+ | 0.0121 | 98.0 | 98 | 0.6506 | 0.7333 |
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+ | 0.0121 | 99.0 | 99 | 0.6100 | 0.7667 |
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+ | 0.0088 | 100.0 | 100 | 0.4137 | 0.8333 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.4.0
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
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