62 lines
1.5 KiB
Markdown
62 lines
1.5 KiB
Markdown
---
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library_name: transformers
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license: mit
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base_model: HFS26/reuters-gpt2-text-gen
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tags:
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- generated_from_trainer
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model-index:
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- name: reuters-gpt2-text-gen
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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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# reuters-gpt2-text-gen
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This model is a fine-tuned version of [HFS26/reuters-gpt2-text-gen](https://huggingface.co/HFS26/reuters-gpt2-text-gen) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 4.7212
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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: 0.0005
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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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- gradient_accumulation_steps: 8
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- total_train_batch_size: 64
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- num_epochs: 1
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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 |
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|:-------------:|:-----:|:----:|:---------------:|
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| 4.5445 | 1.0 | 270 | 4.7212 |
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### Framework versions
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- Transformers 5.0.0
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- Pytorch 2.10.0+cu128
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- Datasets 4.8.3
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- Tokenizers 0.22.2
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