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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: climatebert/distilroberta-base-climate-f
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: CONDITIONAL-multilabel-climatebert
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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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+ # CONDITIONAL-multilabel-climatebert
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+
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+ This model is a fine-tuned version of [climatebert/distilroberta-base-climate-f](https://huggingface.co/climatebert/distilroberta-base-climate-f) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5460
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+ - Precision-micro: 0.5020
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+ - Precision-samples: 0.1954
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+ - Precision-weighted: 0.5047
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+ - Recall-micro: 0.7530
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+ - Recall-samples: 0.1937
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+ - Recall-weighted: 0.7530
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+ - F1-micro: 0.6024
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+ - F1-samples: 0.1927
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+ - F1-weighted: 0.6033
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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: 6.03e-05
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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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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 300
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+ - num_epochs: 6
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision-micro | Precision-samples | Precision-weighted | Recall-micro | Recall-samples | Recall-weighted | F1-micro | F1-samples | F1-weighted |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------------:|:-----------------:|:------------------:|:------------:|:--------------:|:---------------:|:--------:|:----------:|:-----------:|
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+ | 0.5644 | 1.0 | 369 | 0.4161 | 0.3642 | 0.1391 | 0.4167 | 0.5640 | 0.1416 | 0.5640 | 0.4426 | 0.1389 | 0.4372 |
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+ | 0.429 | 2.0 | 738 | 0.3616 | 0.4420 | 0.1803 | 0.4794 | 0.6860 | 0.1769 | 0.6860 | 0.5376 | 0.1768 | 0.5473 |
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+ | 0.2657 | 3.0 | 1107 | 0.4233 | 0.4126 | 0.1950 | 0.4229 | 0.7774 | 0.1987 | 0.7774 | 0.5391 | 0.1944 | 0.5418 |
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+ | 0.1482 | 4.0 | 1476 | 0.4301 | 0.4910 | 0.1891 | 0.4944 | 0.7470 | 0.1908 | 0.7470 | 0.5925 | 0.1882 | 0.5924 |
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+ | 0.069 | 5.0 | 1845 | 0.5016 | 0.5126 | 0.1920 | 0.5193 | 0.7439 | 0.1912 | 0.7439 | 0.6070 | 0.1899 | 0.6090 |
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+ | 0.0353 | 6.0 | 2214 | 0.5460 | 0.5020 | 0.1954 | 0.5047 | 0.7530 | 0.1937 | 0.7530 | 0.6024 | 0.1927 | 0.6033 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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