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---
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license: apache-2.0
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pipeline_tag: text-generation
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language:
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- ru
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tags:
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- generated_from_trainer
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base_model: mistralai/Mistral-7B-v0.1
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datasets:
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- danasone/wikipedia_ru
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model-index:
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- name: Mistral-7B-wikipedia_ru_pruned-0.1_merged
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results: []
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---
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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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<details><summary>See axolotl config</summary>
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axolotl version: `0.4.0`
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```yaml
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base_model: mistralai/Mistral-7B-v0.1
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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is_mistral_derived_model: true
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load_in_8bit: false
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load_in_4bit: true
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strict: false
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datasets:
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- path: ./datasets/ruwiki-pruned
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type: completion
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field: text
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.01
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output_dir: ./models/output
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adapter: qlora
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lora_model_dir:
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sequence_len: 1024
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sample_packing: true
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pad_to_sequence_len: true
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lora_r: 32
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_linear: true
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lora_fan_in_fan_out:
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lora_target_modules:
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- gate_proj
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- down_proj
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- up_proj
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- q_proj
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- v_proj
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- k_proj
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- o_proj
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wandb_project:
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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gradient_accumulation_steps: 1
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micro_batch_size: 11
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num_epochs: 1
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps:
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xformers_attention:
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flash_attention: true
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loss_watchdog_threshold: 5.0
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loss_watchdog_patience: 3
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warmup_steps: 10
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evals_per_epoch:
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eval_table_size:
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eval_max_new_tokens: 128
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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```
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</details><br>
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# Mistral-7B-wikipedia_ru_pruned-0.1_merged
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This model is a merge of [WlappaAI/Mistral-7B-v0.1-wikipedia_ru_pruned-0.1](https://huggingface.co/WlappaAI/Mistral-7B-v0.1-wikipedia_ru_pruned-0.1) together with [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1). It's trained on modified [danasone/wikipedia_ru](https://huggingface.co/datasets/danasone/wikipedia_ru) dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1876
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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: 0.0002
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- train_batch_size: 11
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- eval_batch_size: 11
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- seed: 42
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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: 10
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.5643 | 0.0 | 0 | |
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| 1.012 | 1.0 | 1100 | 1.1876 |
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.40.0.dev0
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- Pytorch 2.2.2+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.0 |
