End of training
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README.md
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---
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license: mit
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base_model: roberta-base
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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: roberta-base-finetuned-nlp-letters-TEXT-all-class-weighted
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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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# roberta-base-finetuned-nlp-letters-TEXT-all-class-weighted
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7120
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- F1: 0.7740
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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: 5e-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: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 10
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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 | 1.0 | 221 | 0.4726 | 0.4302 |
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| No log | 2.0 | 442 | 0.4392 | 0.4995 |
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| 0.4877 | 3.0 | 663 | 0.3867 | 0.4836 |
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| 0.4877 | 4.0 | 884 | 0.5359 | 0.6492 |
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| 0.4029 | 5.0 | 1105 | 0.4401 | 0.6013 |
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| 0.4029 | 6.0 | 1326 | 0.4508 | 0.7301 |
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| 0.3208 | 7.0 | 1547 | 0.7120 | 0.7740 |
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| 0.3208 | 8.0 | 1768 | 1.0509 | 0.7690 |
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| 0.3208 | 9.0 | 1989 | 1.5755 | 0.7444 |
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| 0.2085 | 10.0 | 2210 | 1.8282 | 0.7580 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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