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--- |
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license: mit |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: openai-community/gpt2 |
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datasets: |
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- financial_phrasebank |
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metrics: |
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- accuracy |
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model-index: |
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- name: gpt2-sentiment_analysis |
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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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# gpt2-sentiment_analysis |
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This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the financial_phrasebank dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6571 |
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- Accuracy: {'accuracy': 0.8239339752407153} |
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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: 0.0006 |
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- train_batch_size: 4 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------------------------------:| |
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| No log | 0.9981 | 257 | 0.4654 | {'accuracy': 0.8239339752407153} | |
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| 0.6288 | 2.0 | 515 | 0.4266 | {'accuracy': 0.8266850068775791} | |
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| 0.6288 | 2.9981 | 772 | 0.4558 | {'accuracy': 0.8225584594222833} | |
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| 0.3201 | 4.0 | 1030 | 0.4550 | {'accuracy': 0.811554332874828} | |
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| 0.3201 | 4.9981 | 1287 | 0.4223 | {'accuracy': 0.8294360385144429} | |
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| 0.2464 | 6.0 | 1545 | 0.4637 | {'accuracy': 0.8335625859697386} | |
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| 0.2464 | 6.9981 | 1802 | 0.5243 | {'accuracy': 0.8184319119669876} | |
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| 0.1859 | 8.0 | 2060 | 0.5482 | {'accuracy': 0.8335625859697386} | |
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| 0.1859 | 8.9981 | 2317 | 0.6443 | {'accuracy': 0.8335625859697386} | |
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| 0.1381 | 9.9806 | 2570 | 0.6571 | {'accuracy': 0.8239339752407153} | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
