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--- |
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license: mit |
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tags: |
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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: newsdiscourse-model |
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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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# newsdiscourse-model |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9458 |
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- F1: 0.5610 |
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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: 1 |
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- eval_batch_size: 1 |
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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: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 0.14 | 100 | 1.4843 | 0.2881 | |
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| No log | 0.28 | 200 | 1.3307 | 0.3841 | |
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| No log | 0.43 | 300 | 1.2427 | 0.3991 | |
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| No log | 0.57 | 400 | 1.2590 | 0.4899 | |
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| 1.2399 | 0.71 | 500 | 1.2648 | 0.4658 | |
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| 1.2399 | 0.85 | 600 | 1.2064 | 0.4988 | |
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| 1.2399 | 1.0 | 700 | 1.2564 | 0.4668 | |
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| 1.2399 | 1.14 | 800 | 1.2062 | 0.4912 | |
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| 1.2399 | 1.28 | 900 | 1.1202 | 0.4904 | |
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| 0.9315 | 1.42 | 1000 | 1.1924 | 0.5188 | |
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| 0.9315 | 1.57 | 1100 | 1.1627 | 0.5034 | |
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| 0.9315 | 1.71 | 1200 | 1.1093 | 0.5111 | |
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| 0.9315 | 1.85 | 1300 | 1.1332 | 0.5166 | |
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| 0.9315 | 1.99 | 1400 | 1.1558 | 0.5285 | |
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| 0.8604 | 2.14 | 1500 | 1.2531 | 0.5122 | |
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| 0.8604 | 2.28 | 1600 | 1.2830 | 0.5414 | |
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| 0.8604 | 2.42 | 1700 | 1.2550 | 0.5335 | |
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| 0.8604 | 2.56 | 1800 | 1.1928 | 0.5120 | |
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| 0.8604 | 2.71 | 1900 | 1.2441 | 0.5308 | |
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| 0.7406 | 2.85 | 2000 | 1.2791 | 0.5400 | |
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| 0.7406 | 2.99 | 2100 | 1.2354 | 0.5485 | |
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| 0.7406 | 3.13 | 2200 | 1.3047 | 0.5258 | |
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| 0.7406 | 3.28 | 2300 | 1.3636 | 0.5640 | |
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| 0.7406 | 3.42 | 2400 | 1.2963 | 0.5747 | |
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| 0.6355 | 3.56 | 2500 | 1.2897 | 0.5123 | |
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| 0.6355 | 3.7 | 2600 | 1.3225 | 0.5481 | |
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| 0.6355 | 3.85 | 2700 | 1.3197 | 0.5467 | |
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| 0.6355 | 3.99 | 2800 | 1.2346 | 0.5353 | |
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| 0.6355 | 4.13 | 2900 | 1.3397 | 0.5629 | |
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| 0.5698 | 4.27 | 3000 | 1.4259 | 0.5622 | |
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| 0.5698 | 4.42 | 3100 | 1.3702 | 0.5607 | |
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| 0.5698 | 4.56 | 3200 | 1.4294 | 0.5584 | |
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| 0.5698 | 4.7 | 3300 | 1.5041 | 0.5459 | |
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| 0.5698 | 4.84 | 3400 | 1.4156 | 0.5394 | |
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| 0.5069 | 4.99 | 3500 | 1.4384 | 0.5527 | |
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| 0.5069 | 5.13 | 3600 | 1.5322 | 0.5439 | |
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| 0.5069 | 5.27 | 3700 | 1.4899 | 0.5557 | |
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| 0.5069 | 5.41 | 3800 | 1.4526 | 0.5391 | |
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| 0.5069 | 5.56 | 3900 | 1.5027 | 0.5607 | |
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| 0.4127 | 5.7 | 4000 | 1.5458 | 0.5662 | |
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| 0.4127 | 5.84 | 4100 | 1.5080 | 0.5537 | |
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| 0.4127 | 5.98 | 4200 | 1.5936 | 0.5483 | |
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| 0.4127 | 6.13 | 4300 | 1.7079 | 0.5401 | |
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| 0.4127 | 6.27 | 4400 | 1.5939 | 0.5521 | |
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| 0.3574 | 6.41 | 4500 | 1.5588 | 0.5702 | |
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| 0.3574 | 6.55 | 4600 | 1.6363 | 0.5568 | |
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| 0.3574 | 6.7 | 4700 | 1.6629 | 0.5535 | |
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| 0.3574 | 6.84 | 4800 | 1.6523 | 0.5662 | |
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| 0.3574 | 6.98 | 4900 | 1.7245 | 0.5461 | |
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| 0.3417 | 7.12 | 5000 | 1.6766 | 0.5629 | |
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| 0.3417 | 7.26 | 5100 | 1.8219 | 0.5450 | |
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| 0.3417 | 7.41 | 5200 | 1.7422 | 0.5533 | |
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| 0.3417 | 7.55 | 5300 | 1.8250 | 0.5564 | |
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| 0.3417 | 7.69 | 5400 | 1.7744 | 0.5600 | |
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| 0.2852 | 7.83 | 5500 | 1.7919 | 0.5549 | |
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| 0.2852 | 7.98 | 5600 | 1.7604 | 0.5639 | |
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| 0.2852 | 8.12 | 5700 | 1.7660 | 0.5599 | |
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| 0.2852 | 8.26 | 5800 | 1.7323 | 0.5600 | |
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| 0.2852 | 8.4 | 5900 | 1.9174 | 0.5529 | |
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| 0.2606 | 8.55 | 6000 | 1.8664 | 0.5611 | |
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| 0.2606 | 8.69 | 6100 | 1.9191 | 0.5568 | |
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| 0.2606 | 8.83 | 6200 | 1.8900 | 0.5565 | |
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| 0.2606 | 8.97 | 6300 | 1.9376 | 0.5524 | |
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| 0.2606 | 9.12 | 6400 | 1.9220 | 0.5594 | |
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| 0.2274 | 9.26 | 6500 | 1.9188 | 0.5585 | |
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| 0.2274 | 9.4 | 6600 | 1.9459 | 0.5527 | |
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| 0.2274 | 9.54 | 6700 | 1.9439 | 0.5543 | |
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| 0.2274 | 9.69 | 6800 | 1.9437 | 0.5596 | |
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| 0.2274 | 9.83 | 6900 | 1.9484 | 0.5581 | |
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| 0.2258 | 9.97 | 7000 | 1.9458 | 0.5610 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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