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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert/distilroberta-base |
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tags: |
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- generated_from_trainer |
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- sentiment_analysis |
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model-index: |
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- name: go-emotions-fine-tuned-distilroberta |
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results: [] |
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datasets: |
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- google-research-datasets/go_emotions |
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language: |
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- en |
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metrics: |
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- recall |
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- precision |
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- f1 |
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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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# go-emotions-fine-tuned-distilroberta |
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This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0841 |
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- Micro Precision: 0.6789 |
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- Micro Recall: 0.5047 |
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- Micro F1: 0.5790 |
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- Macro Precision: 0.5559 |
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- Macro Recall: 0.4000 |
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- Macro F1: 0.4502 |
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- Weighted Precision: 0.6538 |
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- Weighted Recall: 0.5047 |
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- Weighted F1: 0.5577 |
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- Hamming Loss: 0.0308 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Micro Precision | Micro Recall | Micro F1 | Macro Precision | Macro Recall | Macro F1 | Weighted Precision | Weighted Recall | Weighted F1 | Hamming Loss | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|:------------:| |
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| 0.1062 | 1.0 | 5427 | 0.0889 | 0.6956 | 0.4498 | 0.5464 | 0.5087 | 0.3111 | 0.3537 | 0.6246 | 0.4498 | 0.4936 | 0.0314 | |
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| 0.0828 | 2.0 | 10854 | 0.0834 | 0.7042 | 0.4798 | 0.5707 | 0.5874 | 0.3562 | 0.4108 | 0.6872 | 0.4798 | 0.5306 | 0.0303 | |
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| 0.0704 | 3.0 | 16281 | 0.0841 | 0.6789 | 0.5047 | 0.5790 | 0.5559 | 0.4000 | 0.4502 | 0.6538 | 0.5047 | 0.5577 | 0.0308 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.21.0 |
