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xlnet-base-cased-airlines-news-multi-label

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End of training

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  1. README.md +50 -26
  2. config.json +5 -5
  3. model.safetensors +2 -2
  4. runs/Jun05_02-36-02_1436e3d6cad1/events.out.tfevents.1717554967.1436e3d6cad1.2748.0 +3 -0
  5. runs/Jun05_02-36-02_1436e3d6cad1/events.out.tfevents.1717555081.1436e3d6cad1.2748.1 +3 -0
  6. runs/Jun05_02-36-02_1436e3d6cad1/events.out.tfevents.1717558335.1436e3d6cad1.2748.2 +3 -0
  7. training_args.bin +1 -1
README.md CHANGED
@@ -5,7 +5,6 @@ tags:
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  - generated_from_trainer
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  metrics:
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  - f1
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- - accuracy
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  model-index:
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  - name: xlnet-base-cased-airlines-news-multi-label
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  results: []
@@ -18,10 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/xlnet-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2822
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- - F1: 0.6647
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- - Roc Auc: 0.8080
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- - Accuracy: 0.6116
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  ## Model description
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@@ -40,38 +38,64 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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  - train_batch_size: 12
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  - eval_batch_size: 12
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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: 15
 
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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- | No log | 1.0 | 150 | 0.2088 | 0.5979 | 0.7399 | 0.6027 |
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- | No log | 2.0 | 300 | 0.1928 | 0.6596 | 0.7725 | 0.6562 |
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- | No log | 3.0 | 450 | 0.2049 | 0.6327 | 0.7653 | 0.5982 |
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- | 0.2167 | 4.0 | 600 | 0.2226 | 0.6506 | 0.8007 | 0.6027 |
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- | 0.2167 | 5.0 | 750 | 0.2280 | 0.6288 | 0.7666 | 0.5893 |
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- | 0.2167 | 6.0 | 900 | 0.2418 | 0.6295 | 0.7709 | 0.5938 |
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- | 0.0812 | 7.0 | 1050 | 0.2610 | 0.6258 | 0.7722 | 0.5982 |
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- | 0.0812 | 8.0 | 1200 | 0.2756 | 0.6098 | 0.7606 | 0.5804 |
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- | 0.0812 | 9.0 | 1350 | 0.2822 | 0.6647 | 0.8080 | 0.6116 |
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- | 0.0325 | 10.0 | 1500 | 0.2908 | 0.6378 | 0.7873 | 0.5938 |
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- | 0.0325 | 11.0 | 1650 | 0.3050 | 0.6319 | 0.7860 | 0.5938 |
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- | 0.0325 | 12.0 | 1800 | 0.3044 | 0.6277 | 0.7830 | 0.5804 |
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- | 0.0325 | 13.0 | 1950 | 0.3030 | 0.6254 | 0.7804 | 0.5804 |
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- | 0.015 | 14.0 | 2100 | 0.3057 | 0.6319 | 0.7860 | 0.5848 |
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- | 0.015 | 15.0 | 2250 | 0.3013 | 0.6168 | 0.7744 | 0.5670 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.41.0
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  - Pytorch 2.3.0+cu121
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- - Datasets 2.19.1
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  - Tokenizers 0.19.1
 
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  - generated_from_trainer
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  metrics:
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  - f1
 
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  model-index:
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  - name: xlnet-base-cased-airlines-news-multi-label
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  results: []
 
17
 
18
  This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/xlnet-base-cased) on the None dataset.
19
  It achieves the following results on the evaluation set:
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+ - Loss: 0.2567
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+ - F1: 0.8989
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+ - Roc Auc: 0.6475
 
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  ## Model description
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38
  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 7e-05
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  - train_batch_size: 12
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  - eval_batch_size: 12
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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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+ - lr_scheduler_warmup_steps: 150
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+ - num_epochs: 40
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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+ | No log | 1.0 | 170 | 0.2834 | 0.8827 | 0.5576 |
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+ | No log | 2.0 | 340 | 0.2670 | 0.8918 | 0.6102 |
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+ | 0.2923 | 3.0 | 510 | 0.2567 | 0.8989 | 0.6475 |
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+ | 0.2923 | 4.0 | 680 | 0.2526 | 0.8910 | 0.6685 |
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+ | 0.2923 | 5.0 | 850 | 0.2512 | 0.8825 | 0.6352 |
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+ | 0.2571 | 6.0 | 1020 | 0.2514 | 0.8863 | 0.6708 |
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+ | 0.2571 | 7.0 | 1190 | 0.2454 | 0.8872 | 0.6490 |
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+ | 0.2571 | 8.0 | 1360 | 0.2495 | 0.8884 | 0.6660 |
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+ | 0.2468 | 9.0 | 1530 | 0.2467 | 0.8881 | 0.6725 |
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+ | 0.2468 | 10.0 | 1700 | 0.2554 | 0.8815 | 0.6514 |
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+ | 0.2468 | 11.0 | 1870 | 0.2474 | 0.8883 | 0.6603 |
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+ | 0.2363 | 12.0 | 2040 | 0.2478 | 0.8912 | 0.6943 |
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+ | 0.2363 | 13.0 | 2210 | 0.2492 | 0.8964 | 0.6976 |
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+ | 0.2363 | 14.0 | 2380 | 0.2530 | 0.8936 | 0.7121 |
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+ | 0.2332 | 15.0 | 2550 | 0.2497 | 0.8893 | 0.6830 |
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+ | 0.2332 | 16.0 | 2720 | 0.2483 | 0.8922 | 0.7008 |
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+ | 0.2332 | 17.0 | 2890 | 0.2489 | 0.8905 | 0.6782 |
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+ | 0.23 | 18.0 | 3060 | 0.2496 | 0.8877 | 0.6927 |
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+ | 0.23 | 19.0 | 3230 | 0.2494 | 0.8855 | 0.6652 |
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+ | 0.23 | 20.0 | 3400 | 0.2483 | 0.8929 | 0.6903 |
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+ | 0.2246 | 21.0 | 3570 | 0.2503 | 0.8902 | 0.6838 |
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+ | 0.2246 | 22.0 | 3740 | 0.2506 | 0.8854 | 0.6805 |
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+ | 0.2246 | 23.0 | 3910 | 0.2515 | 0.8900 | 0.6887 |
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+ | 0.2214 | 24.0 | 4080 | 0.2501 | 0.8894 | 0.6773 |
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+ | 0.2214 | 25.0 | 4250 | 0.2528 | 0.8878 | 0.6870 |
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+ | 0.2214 | 26.0 | 4420 | 0.2519 | 0.8918 | 0.6895 |
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+ | 0.2203 | 27.0 | 4590 | 0.2558 | 0.8897 | 0.6830 |
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+ | 0.2203 | 28.0 | 4760 | 0.2554 | 0.8919 | 0.6952 |
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+ | 0.2203 | 29.0 | 4930 | 0.2537 | 0.8957 | 0.7025 |
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+ | 0.2193 | 30.0 | 5100 | 0.2513 | 0.8951 | 0.7025 |
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+ | 0.2193 | 31.0 | 5270 | 0.2565 | 0.8946 | 0.7130 |
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+ | 0.2193 | 32.0 | 5440 | 0.2542 | 0.8935 | 0.6960 |
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+ | 0.2178 | 33.0 | 5610 | 0.2545 | 0.8970 | 0.7090 |
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+ | 0.2178 | 34.0 | 5780 | 0.2546 | 0.8960 | 0.7138 |
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+ | 0.2178 | 35.0 | 5950 | 0.2550 | 0.8942 | 0.7073 |
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+ | 0.2173 | 36.0 | 6120 | 0.2545 | 0.8942 | 0.7073 |
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+ | 0.2173 | 37.0 | 6290 | 0.2537 | 0.8925 | 0.7008 |
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+ | 0.2173 | 38.0 | 6460 | 0.2541 | 0.8942 | 0.7073 |
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+ | 0.2164 | 39.0 | 6630 | 0.2537 | 0.8940 | 0.7016 |
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+ | 0.2164 | 40.0 | 6800 | 0.2540 | 0.8942 | 0.7073 |
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  ### Framework versions
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+ - Transformers 4.41.1
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  - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.2
101
  - Tokenizers 0.19.1
config.json CHANGED
@@ -16,8 +16,8 @@
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  "ff_activation": "gelu",
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  "id2label": {
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  "0": "capacity expansion",
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- "1": "market expansion",
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- "2": "marketing",
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  "3": "merger & acquisition and finance investments",
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  "4": "outsourcing and alliance",
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  "5": "product introductions and improvements"
@@ -25,8 +25,8 @@
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  "initializer_range": 0.02,
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  "label2id": {
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  "capacity expansion": 0,
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- "market expansion": 1,
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- "marketing": 2,
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  "merger & acquisition and finance investments": 3,
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  "outsourcing and alliance": 4,
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  "product introductions and improvements": 5
@@ -52,7 +52,7 @@
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  }
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  },
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  "torch_dtype": "float32",
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- "transformers_version": "4.41.0",
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  "untie_r": true,
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  "use_mems_eval": true,
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  "use_mems_train": false,
 
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  "ff_activation": "gelu",
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  "id2label": {
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  "0": "capacity expansion",
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+ "1": "legal action",
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+ "2": "market expansion",
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  "3": "merger & acquisition and finance investments",
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  "4": "outsourcing and alliance",
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  "5": "product introductions and improvements"
 
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  "initializer_range": 0.02,
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  "label2id": {
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  "capacity expansion": 0,
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+ "legal action": 1,
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+ "market expansion": 2,
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  "merger & acquisition and finance investments": 3,
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  "outsourcing and alliance": 4,
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  "product introductions and improvements": 5
 
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  }
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  },
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  "torch_dtype": "float32",
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+ "transformers_version": "4.41.1",
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  "untie_r": true,
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  "use_mems_eval": true,
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  "use_mems_train": false,
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