Instructions to use TransferGraph/moshew_bert-mini-sst2-distilled-finetuned-lora-tweet_eval_irony with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use TransferGraph/moshew_bert-mini-sst2-distilled-finetuned-lora-tweet_eval_irony with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("moshew/bert-mini-sst2-distilled") model = PeftModel.from_pretrained(base_model, "TransferGraph/moshew_bert-mini-sst2-distilled-finetuned-lora-tweet_eval_irony") - Notebooks
- Google Colab
- Kaggle
Finished training.
Browse files- README.md +10 -10
- adapter_config.json +2 -2
- adapter_model.safetensors +1 -1
README.md
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args: irony
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metrics:
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- type: accuracy
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name: accuracy
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---
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@@ -33,7 +33,7 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [moshew/bert-mini-sst2-distilled](https://huggingface.co/moshew/bert-mini-sst2-distilled) on the tweet_eval dataset.
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It achieves the following results on the evaluation set:
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## Model description
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| accuracy | train_loss | epoch |
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| 0.5487 | None | 0 |
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### Framework versions
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args: irony
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metrics:
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- type: accuracy
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value: 0.6115183246073298
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name: accuracy
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---
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This model is a fine-tuned version of [moshew/bert-mini-sst2-distilled](https://huggingface.co/moshew/bert-mini-sst2-distilled) on the tweet_eval dataset.
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It achieves the following results on the evaluation set:
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- accuracy: 0.6115
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## Model description
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| accuracy | train_loss | epoch |
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|:--------:|:----------:|:-----:|
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| 0.5487 | None | 0 |
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| 0.5707 | 0.6844 | 0 |
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| 0.6199 | 0.6719 | 1 |
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| 0.6115 | 0.6333 | 6 |
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### Framework versions
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adapter_config.json
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"rank_pattern": {},
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"target_modules": [
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"task_type": "SEQ_CLS",
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"use_rslora": false
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"task_type": "SEQ_CLS",
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"use_rslora": false
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adapter_model.safetensors
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