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README.md
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model-index:
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- name: openhermes-mistral-cat_out
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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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# openhermes-mistral-cat_out
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This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6083
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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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- learning_rate: 0.0002
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_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: 14
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- num_epochs: 2
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss |
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| 1.6981 | 1.01 | 61 | 1.6273 |
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| 1.6355 | 1.96 | 120 | 1.6083 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: True
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- bnb_4bit_compute_dtype: float16
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### Framework versions
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- PEFT 0.6.0
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model-index:
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- name: openhermes-mistral-cat_out
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results: []
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datasets:
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- xaviviro/oasst2_ca_gpt
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language:
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- ca
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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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# OpenHermes-2.5-Mistral-7B-Catala-LoRA
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This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on the [xaviviro/oasst2_ca_gpt](https://huggingface.co/datasets/xaviviro/oasst2_ca_gpt) dataset.
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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