Technoculture
/

MT7Bi-alpha

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 ---
 library_name: peft
 base_model: epfl-llm/meditron-7b
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
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 ## Training procedure

 ---
+license: llama2
 library_name: peft
+tags:
+- axolotl
+- generated_from_trainer
 base_model: epfl-llm/meditron-7b
+model-index:
+- name: md7b-alpha
+  results: []
 ---
+<!-- 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: `0.3.0`
+```yaml
+base_model: epfl-llm/meditron-7b
+model_type: LlamaForCausalLM
+tokenizer_type: LlamaTokenizer
+is_llama_derived_model: true
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+datasets:
+  - path: Open-Orca/SlimOrca-Dedup
+    type: sharegpt
+  - path: axiong/pmc_llama_instructions
+    type: alpaca
+  - path: xzuyn/chatdoctor-200k-stripped
+    type: alpaca
+  - path: technoculture/riddle_sense
+    type: alpaca
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./qlora-out
+adapter: qlora
+lora_model_dir:
+sequence_len: 2048
+sample_packing: true
+pad_to_sequence_len: true
+lora_r: 32
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_modules:
+lora_target_linear: true
+lora_fan_in_fan_out:
+wandb_project: MD7b-alpha
+wandb_entity: technoculture
+wandb_watch:
+wandb_name:
+wandb_log_model: true
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 4
+optimizer: paged_adamw_32bit
+lr_scheduler_type: cosine
+lr_scheduler: cosine
+learning_rate: 0.0003
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+tf32: false
+do_eval: true
+evals_per_epoch: 2
+eval_table_size:
+saves_per_epoch: 1
+hub_model_id: technoculture/md7b-alpha
+hub_strategy: every_save
+push_to_hub: true
+log_level: info
+logging_steps: 1
+logging_strategy: steps
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint: false
+local_rank:
+xformers_attention:
+flash_attention: true
+warmup_steps: 2000
+debug:
+deepspeed:
+weight_decay: 0.1
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<s>"
+  eos_token: "</s>"
+  unk_token: "<unk>"
+```
+</details><br>
+# md7b-alpha
+This model is a fine-tuned version of [epfl-llm/meditron-7b](https://huggingface.co/epfl-llm/meditron-7b) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0238
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 0.0003
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- 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: 2000
+- num_epochs: 4
+### Training results
+| Training Loss | Epoch | Step   | Validation Loss |
+|:-------------:|:-----:|:------:|:---------------:|
+| 2.1602        | 0.0   | 1      | 1.9066          |
+| 1.1128        | 0.5   | 14744  | 1.1620          |
+| 1.2463        | 1.0   | 29488  | 1.1288          |
+| 0.8291        | 1.49  | 44232  | 1.1025          |
+| 1.0524        | 1.99  | 58976  | 1.0771          |
+| 1.0369        | 2.48  | 73720  | 1.0563          |
+| 1.0402        | 2.98  | 88464  | 1.0299          |
+| 0.943         | 3.47  | 103208 | 1.0271          |
+| 1.0845        | 3.97  | 117952 | 1.0238          |
+### Framework versions
+- Transformers 4.37.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0
 ## Training procedure

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