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--- |
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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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base_model: cardiffnlp/twitter-roberta-base-sentiment-latest |
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model-index: |
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- name: twitter-roberta-base-sentiment-latest-finetuned-FG-CONCAT_SENTENCE-H-NEWS |
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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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# twitter-roberta-base-sentiment-latest-finetuned-FG-CONCAT_SENTENCE-H-NEWS |
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6335 |
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- Accuracy: 0.5275 |
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- F1: 0.5198 |
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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: 6e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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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: 20 |
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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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| No log | 1.0 | 61 | 1.0568 | 0.4396 | 0.2684 | |
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| No log | 2.0 | 122 | 1.0518 | 0.4396 | 0.2684 | |
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| No log | 3.0 | 183 | 1.0584 | 0.4396 | 0.2684 | |
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| No log | 4.0 | 244 | 1.1720 | 0.3956 | 0.3223 | |
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| No log | 5.0 | 305 | 1.2473 | 0.5275 | 0.5196 | |
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| No log | 6.0 | 366 | 1.0789 | 0.5220 | 0.5301 | |
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| No log | 7.0 | 427 | 1.3556 | 0.5604 | 0.5426 | |
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| No log | 8.0 | 488 | 1.7314 | 0.5330 | 0.5158 | |
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| 0.8045 | 9.0 | 549 | 2.2774 | 0.5330 | 0.5161 | |
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| 0.8045 | 10.0 | 610 | 2.8362 | 0.4451 | 0.4512 | |
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| 0.8045 | 11.0 | 671 | 2.9130 | 0.5275 | 0.4931 | |
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| 0.8045 | 12.0 | 732 | 3.1023 | 0.5110 | 0.5010 | |
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| 0.8045 | 13.0 | 793 | 3.2670 | 0.5385 | 0.5208 | |
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| 0.8045 | 14.0 | 854 | 3.4151 | 0.4945 | 0.4856 | |
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| 0.8045 | 15.0 | 915 | 3.7614 | 0.4615 | 0.4458 | |
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| 0.8045 | 16.0 | 976 | 3.5224 | 0.5220 | 0.5122 | |
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| 0.0535 | 17.0 | 1037 | 3.5196 | 0.5165 | 0.5102 | |
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| 0.0535 | 18.0 | 1098 | 3.5791 | 0.5110 | 0.5039 | |
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| 0.0535 | 19.0 | 1159 | 3.6220 | 0.5220 | 0.5137 | |
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| 0.0535 | 20.0 | 1220 | 3.6335 | 0.5275 | 0.5198 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.9.1 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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