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--- |
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license: apache-2.0 |
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datasets: |
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- dair-ai/emotion |
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language: |
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- en |
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metrics: |
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- f1 |
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- accuracy |
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base_model: |
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- distilbert-base-uncased |
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library_name: transformers |
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pipeline_tag: text-classification |
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tags: |
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- distilbert |
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- pytorch |
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- emotion |
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- trainer |
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widget: |
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- text: "Interview preparation, I hate talking about myself, one dull subject matter!" |
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- text: "I'm in such a happy mood today i feel almost delighted and i havent done anything different today then i normally have it is wonderful" |
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- text: "I had every intention of doing more gardening this morning while it was still cool but i was just feeling so rotten" |
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- text: "Wow! I'm really impressed that Ashley can speak 7 languages, whereas I only speak one!" |
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- text: "No one wants to win the wild card because you have to play the Cubs on the road." |
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- text: "After Kylie had her heart broken by her ex-boyfriend, she felt so down and blue. I tried to cheer her up, but she just wants to be sad for awhile." |
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- text: "Jamie was in a bar with his friends one night when he saw a beautiful girl. He felt confident that night so he went to go talk to her." |
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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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# distilbert-base-uncased-finetuned-emotion |
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This model is a fine-tuned variant of distilbert-base-uncased using the emotion dataset. The evaluation results demonstrate its performance: |
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- Loss: 0.1595 |
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- Accuracy: 93.35% |
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- F1 Score: 93.35% |
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### Hyperparameters |
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- learning_rate: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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### Training results |
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| Epoch | Training Loss | Validation Loss | Accuracy | F1 |
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|:------:|:---------------:|:-----------------:|:----------:|:----------:| |
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| 1 | 0.1703 | 0.1709 | 0.9355 | 0.9361 | |
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| 2 | 0.1115 | 0.1595 | 0.9335 | 0.9335 | |
