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google/flan_t5_base_amazon/README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/flan-t5-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: flan_t5_base_amazon
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+ results: []
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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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+ # flan_t5_base_amazon
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+
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+ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5448
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+ - Accuracy: 0.8412
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+ - F1 Macro: 0.8142
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+ - F1 Micro: 0.8412
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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: 0.0005
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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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+ - distributed_type: multi-GPU
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+ - num_devices: 2
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+ - total_train_batch_size: 32
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+ - total_eval_batch_size: 32
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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: 3.0
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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 | F1 Macro | F1 Micro |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
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+ | 1.1669 | 0.13 | 50 | 0.9142 | 0.7404 | 0.6916 | 0.7404 |
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+ | 0.8536 | 0.26 | 100 | 0.8417 | 0.7569 | 0.7197 | 0.7569 |
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+ | 0.827 | 0.39 | 150 | 0.6893 | 0.7905 | 0.7471 | 0.7905 |
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+ | 0.672 | 0.53 | 200 | 0.7235 | 0.7984 | 0.7730 | 0.7984 |
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+ | 0.7424 | 0.66 | 250 | 0.6684 | 0.7945 | 0.7461 | 0.7945 |
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+ | 0.6802 | 0.79 | 300 | 0.6008 | 0.8215 | 0.8014 | 0.8215 |
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+ | 0.7847 | 0.92 | 350 | 0.6225 | 0.8123 | 0.7925 | 0.8123 |
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+ | 0.5258 | 1.05 | 400 | 0.6656 | 0.8215 | 0.8000 | 0.8215 |
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+ | 0.4945 | 1.18 | 450 | 0.6410 | 0.8235 | 0.7983 | 0.8235 |
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+ | 0.4097 | 1.32 | 500 | 0.5937 | 0.8347 | 0.8110 | 0.8347 |
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+ | 0.4116 | 1.45 | 550 | 0.5966 | 0.8314 | 0.8061 | 0.8314 |
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+ | 0.4785 | 1.58 | 600 | 0.5696 | 0.8347 | 0.8107 | 0.8347 |
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+ | 0.4821 | 1.71 | 650 | 0.5536 | 0.8366 | 0.8098 | 0.8366 |
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+ | 0.4137 | 1.84 | 700 | 0.5612 | 0.8373 | 0.8116 | 0.8373 |
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+ | 0.4623 | 1.97 | 750 | 0.5448 | 0.8412 | 0.8142 | 0.8412 |
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+ | 0.1953 | 2.11 | 800 | 0.5984 | 0.8472 | 0.8201 | 0.8472 |
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+ | 0.2114 | 2.24 | 850 | 0.6189 | 0.8432 | 0.8177 | 0.8432 |
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+ | 0.2252 | 2.37 | 900 | 0.6411 | 0.8465 | 0.8199 | 0.8465 |
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+ | 0.1937 | 2.5 | 950 | 0.6044 | 0.8524 | 0.8245 | 0.8524 |
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+ | 0.2611 | 2.63 | 1000 | 0.6188 | 0.8472 | 0.8189 | 0.8472 |
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+ | 0.3021 | 2.76 | 1050 | 0.6018 | 0.8472 | 0.8189 | 0.8472 |
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+ | 0.2309 | 2.89 | 1100 | 0.5804 | 0.8478 | 0.8186 | 0.8478 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.0.dev0
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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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+ "test_steps_per_second": 11.015,
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+ "train_loss": 0.5365497335007317,
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+ "train_samples": 12144,
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+ "train_samples_per_second": 72.676,
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+ "train_steps_per_second": 2.274
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+ }
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+ ---
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+ license: apache-2.0
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+ base_model: google/flan-t5-base
4
+ tags:
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+ - generated_from_trainer
6
+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: flan_t5_base_ledgar
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+ results: []
11
+ ---
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+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # flan_t5_base_ledgar
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+
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+ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.5092
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+ - Accuracy: 0.8685
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+ - F1 Macro: 0.7955
23
+ - F1 Micro: 0.8685
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+
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+ ## Model description
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+
27
+ More information needed
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+
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+ ## Intended uses & limitations
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+
31
+ More information needed
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+
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+ ## Training and evaluation data
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+
35
+ 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: 0.0005
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 2
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+ - total_train_batch_size: 64
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+ - total_eval_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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+ - num_epochs: 3.0
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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 | F1 Macro | F1 Micro |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
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+ | 1.2824 | 0.11 | 100 | 1.0243 | 0.7464 | 0.5723 | 0.7464 |
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+ | 0.8961 | 0.21 | 200 | 0.8572 | 0.7743 | 0.6359 | 0.7743 |
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+ | 0.8233 | 0.32 | 300 | 0.7788 | 0.7968 | 0.6756 | 0.7968 |
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+ | 0.7722 | 0.43 | 400 | 0.7432 | 0.8014 | 0.6689 | 0.8014 |
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+ | 0.7739 | 0.53 | 500 | 0.6933 | 0.8135 | 0.7020 | 0.8135 |
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+ | 0.7435 | 0.64 | 600 | 0.6871 | 0.8137 | 0.7028 | 0.8137 |
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+ | 0.6877 | 0.75 | 700 | 0.6751 | 0.8169 | 0.7012 | 0.8169 |
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+ | 0.6968 | 0.85 | 800 | 0.6471 | 0.8225 | 0.7249 | 0.8225 |
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+ | 0.6218 | 0.96 | 900 | 0.6366 | 0.8219 | 0.7264 | 0.8219 |
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+ | 0.5101 | 1.07 | 1000 | 0.6130 | 0.8378 | 0.7388 | 0.8378 |
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+ | 0.5411 | 1.17 | 1100 | 0.6088 | 0.8375 | 0.7392 | 0.8375 |
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+ | 0.5918 | 1.28 | 1200 | 0.5864 | 0.8449 | 0.7577 | 0.8449 |
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+ | 0.4785 | 1.39 | 1300 | 0.5917 | 0.8391 | 0.7460 | 0.8391 |
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+ | 0.4372 | 1.49 | 1400 | 0.5790 | 0.8409 | 0.7563 | 0.8409 |
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+ | 0.5022 | 1.6 | 1500 | 0.5868 | 0.8437 | 0.7524 | 0.8437 |
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+ | 0.5391 | 1.71 | 1600 | 0.5613 | 0.8447 | 0.7520 | 0.8447 |
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+ | 0.4971 | 1.81 | 1700 | 0.5466 | 0.8545 | 0.7702 | 0.8545 |
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+ | 0.4686 | 1.92 | 1800 | 0.5260 | 0.8566 | 0.7774 | 0.8566 |
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+ | 0.349 | 2.03 | 1900 | 0.5416 | 0.8565 | 0.7721 | 0.8565 |
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+ | 0.3216 | 2.13 | 2000 | 0.5441 | 0.8565 | 0.7763 | 0.8565 |
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+ | 0.3531 | 2.24 | 2100 | 0.5444 | 0.8553 | 0.7753 | 0.8553 |
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+ | 0.3276 | 2.35 | 2200 | 0.5380 | 0.8604 | 0.7796 | 0.8604 |
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+ | 0.3372 | 2.45 | 2300 | 0.5231 | 0.8634 | 0.7831 | 0.8634 |
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+ | 0.3227 | 2.56 | 2400 | 0.5210 | 0.8651 | 0.7872 | 0.8651 |
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+ | 0.2987 | 2.67 | 2500 | 0.5188 | 0.8665 | 0.7910 | 0.8665 |
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+ | 0.3354 | 2.77 | 2600 | 0.5150 | 0.8666 | 0.7931 | 0.8666 |
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+ | 0.3103 | 2.88 | 2700 | 0.5103 | 0.8681 | 0.7942 | 0.8681 |
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+ | 0.3248 | 2.99 | 2800 | 0.5092 | 0.8685 | 0.7955 | 0.8685 |
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+
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+
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+ ### Framework versions
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+
90
+ - Transformers 4.39.0.dev0
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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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+ "test_accuracy": 0.8682,
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+ "test_f1_macro": 0.7969025101161749,
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+ "test_samples_per_second": 365.524,
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+ "test_steps_per_second": 5.739,
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