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--- |
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license: apache-2.0 |
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base_model: projecte-aina/roberta-base-ca-v2-cased-te |
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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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- f1 |
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model-index: |
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- name: modelofinenew |
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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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# modelofinenew |
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This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2185 |
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- Accuracy: 0.5126 |
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- F1: 0.5338 |
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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: 20 |
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- eval_batch_size: 2 |
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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: 100 |
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- num_epochs: 30 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:| |
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| 1.9546 | 1.6129 | 50 | 2.5028 | 0.2101 | 0.2019 | |
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| 1.7901 | 3.2258 | 100 | 2.6787 | 0.1849 | 0.1805 | |
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| 1.6177 | 4.8387 | 150 | 2.3416 | 0.3445 | 0.3332 | |
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| 1.2977 | 6.4516 | 200 | 2.0729 | 0.4202 | 0.4060 | |
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| 0.9411 | 8.0645 | 250 | 1.9746 | 0.4706 | 0.4583 | |
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| 0.595 | 9.6774 | 300 | 1.8840 | 0.5126 | 0.5167 | |
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| 0.3374 | 11.2903 | 350 | 1.8955 | 0.4958 | 0.4977 | |
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| 0.1974 | 12.9032 | 400 | 1.9658 | 0.5378 | 0.5169 | |
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| 0.0981 | 14.5161 | 450 | 2.2185 | 0.5126 | 0.5338 | |
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| 0.05 | 16.1290 | 500 | 2.3554 | 0.5042 | 0.5096 | |
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| 0.0312 | 17.7419 | 550 | 2.4366 | 0.5294 | 0.5289 | |
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| 0.0235 | 19.3548 | 600 | 2.5235 | 0.5210 | 0.5181 | |
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| 0.0194 | 20.9677 | 650 | 2.5713 | 0.5294 | 0.5289 | |
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| 0.0166 | 22.5806 | 700 | 2.6188 | 0.5294 | 0.5289 | |
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| 0.0148 | 24.1935 | 750 | 2.6473 | 0.5294 | 0.5289 | |
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| 0.0136 | 25.8065 | 800 | 2.6742 | 0.5210 | 0.5218 | |
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| 0.013 | 27.4194 | 850 | 2.6920 | 0.5210 | 0.5218 | |
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| 0.0129 | 29.0323 | 900 | 2.6961 | 0.5210 | 0.5218 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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