End of training
Browse files- README.md +65 -0
- pytorch_model.bin +1 -1
README.md
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---
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license: apache-2.0
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base_model: distilbert-base-uncased
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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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model-index:
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- name: distilbert_finetuned_claimdecomp
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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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# distilbert_finetuned_claimdecomp
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 9.3205
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- Accuracy: 0.335
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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: 3e-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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- training_steps: 30000
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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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| 0.0064 | 50.0 | 5000 | 5.7963 | 0.375 |
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| 0.0 | 100.0 | 10000 | 7.2917 | 0.36 |
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| 0.0 | 150.0 | 15000 | 7.0473 | 0.33 |
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| 0.0 | 200.0 | 20000 | 8.0988 | 0.31 |
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| 0.0 | 250.0 | 25000 | 8.8824 | 0.325 |
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| 0.0 | 300.0 | 30000 | 9.3205 | 0.335 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.0.0
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- Datasets 2.14.5
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- Tokenizers 0.14.1
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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size 267867821
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version https://git-lfs.github.com/spec/v1
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size 267867821
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