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README.md
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---
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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: pythia-160m-hq-emails-v4
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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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# pythia-160m-hq-emails-v4
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This model is a fine-tuned version of [EleutherAI/pythia-160m-deduped](https://huggingface.co/EleutherAI/pythia-160m-deduped) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.2856
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- Accuracy: 0.6113
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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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- distributed_type: multi-GPU
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- gradient_accumulation_steps: 32
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.05
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- num_epochs: 4.0
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- mixed_precision_training: Native AMP
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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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| 2.412 | 0.99 | 76 | 2.5027 | 0.5458 |
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| 1.9702 | 1.99 | 152 | 2.2757 | 0.5850 |
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| 1.4628 | 2.99 | 228 | 2.2162 | 0.6082 |
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| 1.1662 | 3.99 | 304 | 2.2856 | 0.6113 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.8.0
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- Tokenizers 0.13.1
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