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README.md
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---
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library_name: transformers
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license:
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base_model: meta-llama/Llama-3.3-70B-Instruct
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tags:
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- generated_from_trainer
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model-index:
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- name: dev/shm/EVA-LLaMA-3.33-70B-v0.1
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results: []
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---
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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<details><summary>See axolotl config</summary>
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weight_decay: 0.2
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```
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</details><br>
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# dev/shm/EVA-LLaMA-3.33-70B-v0.1
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This model is a fine-tuned version of [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0225
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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: 1
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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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- num_devices: 8
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 64
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- total_eval_batch_size: 8
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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_steps: 20
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.6108 | 0.0061 | 1 | 1.6226 |
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| 1.0653 | 0.2498 | 41 | 1.0166 |
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| 0.8656 | 0.4996 | 82 | 0.9681 |
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| 0.8904 | 0.7494 | 123 | 0.9443 |
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| 0.9196 | 0.9992 | 164 | 0.9317 |
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| 0.5136 | 1.2451 | 205 | 0.9584 |
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| 0.5903 | 1.4947 | 246 | 0.9509 |
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| 0.544 | 1.7443 | 287 | 0.9394 |
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| 0.5435 | 1.9939 | 328 | 0.9347 |
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| 0.2605 | 2.2420 | 369 | 1.0237 |
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| 0.2796 | 2.4916 | 410 | 1.0240 |
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| 0.305 | 2.7412 | 451 | 1.0220 |
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| 0.2457 | 2.9909 | 492 | 1.0225 |
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### Framework versions
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- Transformers 4.45.1
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- Pytorch 2.5.1+cu124
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- Datasets 2.21.0
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- Tokenizers 0.20.3
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---
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library_name: transformers
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license: other
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license_name: eva-llama3.3
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base_model: meta-llama/Llama-3.3-70B-Instruct
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tags:
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- generated_from_trainer
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model-index:
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- name: dev/shm/EVA-LLaMA-3.33-70B-v0.1
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results: []
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datasets:
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- anthracite-org/kalo-opus-instruct-22k-no-refusal
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- Nopm/Opus_WritingStruct
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- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
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- Gryphe/Sonnet3.5-Charcard-Roleplay
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- Gryphe/ChatGPT-4o-Writing-Prompts
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- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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- nothingiisreal/Reddit-Dirty-And-WritingPrompts
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- allura-org/Celeste-1.x-data-mixture
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- cognitivecomputations/dolphin-2.9.3
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<h1>EVA LLaMA 3.33 70B v0.0</h1>
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<p>
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A RP/storywriting specialist model, full-parameter finetune of Llama-3.3-70B-Instruct on mixture of synthetic and natural data.<br>
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It uses Celeste 70B 0.1 data mixture, greatly expanding it to improve versatility, creativity and "flavor" of the resulting model.<br>
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This model was built with Llama by Meta.<br>
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</p>
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<p>
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<p>Prompt format is ChatML.</p><br>
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<h3>Recommended sampler values:</h3>
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<ul>
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<li>Temperature: 1</li>
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<li>Min-P: 0.05</li>
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<li>Repetition Penalty: 1.03</li>
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</ul>
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<h3>Recommended SillyTavern preset (via CalamitousFelicitousness):</h3>
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<ul><li><a href="https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2/blob/main/EV01.json">Master import</a></li></ul>
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</p>
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<p>
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<br>
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<h3>
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Training data:
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</h3>
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<ul>
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<li>Celeste 70B 0.1 data mixture minus Opus Instruct subset. See that model's <a href=https://huggingface.co/nothingiisreal/L3.1-70B-Celeste-V0.1-BF16>card</a> for details.</li>
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<li>Kalomaze's Opus_Instruct_25k dataset, filtered for refusals.</li>
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<li>A subset (1k rows) of ChatGPT-4o-WritingPrompts by Gryphe</li>
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<li>A subset (2k rows) of Sonnet3.5-Charcards-Roleplay by Gryphe</li>
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<li>Synthstruct and SynthRP datasets by Epiculous</li>
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<li>A subset from Dolphin-2.9.3, including filtered version of not_samantha and a small subset of systemchat.</li>
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</ul>
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<h3>
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Training time and hardware:
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</h3>
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<ul><li>10 hours on 8xH100 SXM</a></li></ul><br>
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</p>
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<p>Model was created by Kearm, Auri and Cahvay.</p>
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<h4>Special thanks:</h4><ul>
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<li>to Cahvay for his work on dataset filtering.</li>
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<li>to Gryphe, Lemmy, Kalomaze, Nopm, Epiculous and CognitiveComputations for the data</li>
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<li>and to Allura-org for support, feedback, beta-testing and doing quality control of EVA models.</li></ul>
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<h3>Licensing</h3>
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<p>Llama-3.3-70B-Instruct by Meta is licensed under <a href=https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct/blob/main/LICENSE>Llama 3.3 Community License Agreement (further referred as L3.3 license)</a> and is a subject to <a href=https://www.llama.com/llama3_3/use-policy>Acceptable Use Policy for Llama Materials</a>.<br>
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This derivative is free for personal, research and commercial use on terms of L3.3 license with one extra clause: <br>
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- Infermatic Inc and any of its employees or paid associates cannot utilize, distribute, download, or otherwise make use of EVA models for any purpose.</p>
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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<details><summary>See axolotl config</summary>
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weight_decay: 0.2
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```
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</details><br>
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