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--- |
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license: apache-2.0 |
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base_model: BEE-spoke-data/smol_llama-101M-GQA |
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tags: |
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- art |
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- text2image |
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- prompt |
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- prompt generator |
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- diffusion util |
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metrics: |
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- accuracy |
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inference: |
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parameters: |
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max_new_tokens: 64 |
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do_sample: true |
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temperature: 0.8 |
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repetition_penalty: 1.15 |
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no_repeat_ngram_size: 4 |
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eta_cutoff: 0.001 |
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renormalize_logits: true |
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widget: |
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- text: avocado chair |
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example_title: avocado chair |
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- text: A mysterious potato |
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example_title: potato |
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pipeline_tag: text-generation |
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datasets: |
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- pszemraj/midjourney-messages-cleaned |
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--- |
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# smol_llama-101M-midjourney-messages |
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Given a 'partial prompt' for a text2image model, this generates additional relevant text to include for a full prompt. |
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dalle3: |
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## Model description |
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This model is a fine-tuned version of [BEE-spoke-data/smol_llama-101M-GQA](https://huggingface.co/BEE-spoke-data/smol_llama-101M-GQA) on the `pszemraj/midjourney-messages-cleaned` dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8431 |
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- Accuracy: 0.4682 |
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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: 0.00025 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 17056 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08 |
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- lr_scheduler_type: inverse_sqrt |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 1.0 |
