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--- |
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base_model: dianamihalache27/Twroberta-baseB_5epoch |
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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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- precision |
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- recall |
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model-index: |
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- name: ceva |
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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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# ceva |
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This model is a fine-tuned version of [dianamihalache27/Twroberta-baseB_5epoch](https://huggingface.co/dianamihalache27/Twroberta-baseB_5epoch) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1932 |
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- Accuracy: 0.7714 |
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- F1: 0.2892 |
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- Precision: 0.2435 |
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- Recall: 0.3579 |
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- Precision Sarcastic: 0.3372 |
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- Recall Sarcastic: 0.4833 |
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- F1 Sarcastic: 0.3973 |
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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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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:| |
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| No log | 1.0 | 217 | 0.1618 | 0.7893 | 0.2947 | 0.2611 | 0.3395 | 0.3458 | 0.4611 | 0.3952 | |
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| No log | 2.0 | 434 | 0.1815 | 0.7629 | 0.3104 | 0.2560 | 0.4059 | 0.3299 | 0.5278 | 0.4060 | |
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| 0.0559 | 3.0 | 651 | 0.1762 | 0.8 | 0.2957 | 0.2991 | 0.3173 | 0.3721 | 0.4444 | 0.4051 | |
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| 0.0559 | 4.0 | 868 | 0.1811 | 0.7636 | 0.2933 | 0.2418 | 0.3727 | 0.3297 | 0.5111 | 0.4009 | |
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| 0.0245 | 5.0 | 1085 | 0.1932 | 0.7714 | 0.2892 | 0.2435 | 0.3579 | 0.3372 | 0.4833 | 0.3973 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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