End of training
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README.md
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---
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license: apache-2.0
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base_model: albert/albert-base-v1
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- accuracy
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model-index:
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- name: toxigen-albert-binary-clsf
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/octoopt/huggingface/runs/39ugf5uc)
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# toxigen-albert-binary-clsf
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This model is a fine-tuned version of [albert/albert-base-v1](https://huggingface.co/albert/albert-base-v1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0000
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- Precision: 1.0000
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- Recall: 1.0000
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- Accuracy: 1.0000
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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: 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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- 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: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|
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| 0.0 | 1.0 | 3137 | 0.0000 | 1.0000 | 1.0000 | 1.0000 |
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| 0.0001 | 2.0 | 6274 | 0.0000 | 1.0000 | 1.0000 | 1.0000 |
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.1.2
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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