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README.md

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+---
+base_model: BEE-spoke-data/Meta-Llama-3-8Bee
+datasets:
+- BEE-spoke-data/bees-internal
+inference: true
+language:
+- en
+license: llama3
+model-index:
+- name: Meta-Llama-3-8Bee
+  results: []
+model_creator: BEE-spoke-data
+model_name: Meta-Llama-3-8Bee
+pipeline_tag: text-generation
+quantized_by: afrideva
+tags:
+- axolotl
+- generated_from_trainer
+- gguf
+- ggml
+- quantized
+---
+
+# Meta-Llama-3-8Bee-GGUF
+
+Quantized GGUF model files for [Meta-Llama-3-8Bee](https://huggingface.co/BEE-spoke-data/Meta-Llama-3-8Bee) from [BEE-spoke-data](https://huggingface.co/BEE-spoke-data)
+
+## Original Model Card:
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<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)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.0`
+```yaml
+base_model: meta-llama/Meta-Llama-3-8B
+model_type: LlamaForCausalLM
+tokenizer_type: AutoTokenizer
+strict: false
+
+# dataset
+datasets:
+    - path: BEE-spoke-data/bees-internal
+      type: completion # format from earlier
+      field: text # Optional[str] default: text, field to use for completion data
+val_set_size: 0.05
+
+sequence_len: 8192
+sample_packing: true
+pad_to_sequence_len: true
+train_on_inputs: false
+group_by_length: false
+
+# WANDB
+wandb_project: llama3-8bee
+wandb_entity: pszemraj
+wandb_watch: gradients
+wandb_name: llama3-8bee-8192
+hub_model_id: pszemraj/Meta-Llama-3-8Bee
+hub_strategy: every_save
+
+gradient_accumulation_steps: 8
+micro_batch_size: 1
+num_epochs: 1
+optimizer: paged_adamw_32bit
+lr_scheduler: cosine
+learning_rate: 2e-5
+
+load_in_8bit: false
+load_in_4bit: false
+bf16: auto
+fp16:
+tf32: true
+
+torch_compile: true # requires >= torch 2.0, may sometimes cause problems
+torch_compile_backend: inductor # Optional[str]
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+early_stopping_patience:
+logging_steps: 10
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 25
+# hyperparams for freq of evals, saving, etc
+evals_per_epoch: 3
+saves_per_epoch: 3
+save_safetensors: true
+save_total_limit: 1 # Checkpoints saved at a time
+output_dir: ./output-axolotl/output-model-gamma
+resume_from_checkpoint:
+
+
+deepspeed:
+weight_decay: 0.0
+
+special_tokens:
+  pad_token: <|end_of_text|>
+```
+
+</details><br>
+
+# Meta-Llama-3-8Bee
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the `BEE-spoke-data/bees-internal` dataset (continued pretraining).
+It achieves the following results on the evaluation set:
+- Loss: 2.3319
+
+## Intended uses & limitations
+
+- unveiling knowledge about bees and apiary practice
+- needs further tuning to be used in 'instruct' type settings
+
+## Training and evaluation data
+
+🐝🍯
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 25
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| No log        | 0.0   | 1    | 2.5339          |
+| 2.3719        | 0.33  | 232  | 2.3658          |
+| 2.2914        | 0.67  | 464  | 2.3319          |
+
+
+### Framework versions
+
+- Transformers 4.40.0.dev0
+- Pytorch 2.3.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0