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---

license: apache-2.0
pipeline_tag: text-generation
language:
  - ru
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
datasets:
  - danasone/wikipedia_ru
model-index:
- name: Mistral-7B-wikipedia_ru_pruned-0.1_merged
  results: []
---



[<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: mistralai/Mistral-7B-v0.1

model_type: MistralForCausalLM

tokenizer_type: LlamaTokenizer

is_mistral_derived_model: true



load_in_8bit: false

load_in_4bit: true

strict: false



datasets:

  - path: ./datasets/ruwiki-pruned

    type: completion

    field: text

dataset_prepared_path: last_run_prepared

val_set_size: 0.01

output_dir: ./models/output



adapter: qlora

lora_model_dir:



sequence_len: 1024

sample_packing: true

pad_to_sequence_len: true



lora_r: 32

lora_alpha: 16

lora_dropout: 0.05

lora_target_linear: true

lora_fan_in_fan_out:

lora_target_modules:

  - gate_proj

  - down_proj

  - up_proj

  - q_proj

  - v_proj

  - k_proj

  - o_proj



wandb_project:

wandb_entity:

wandb_watch:

wandb_name:

wandb_log_model:



gradient_accumulation_steps: 1

micro_batch_size: 11

num_epochs: 1

optimizer: adamw_bnb_8bit

lr_scheduler: cosine

learning_rate: 0.0002



train_on_inputs: false

group_by_length: false

bf16: auto

fp16:

tf32: false



gradient_checkpointing: true

early_stopping_patience:

resume_from_checkpoint:

local_rank:

logging_steps:

xformers_attention:

flash_attention: true



loss_watchdog_threshold: 5.0

loss_watchdog_patience: 3



warmup_steps: 10

evals_per_epoch:

eval_table_size:

eval_max_new_tokens: 128

saves_per_epoch: 1

debug:

deepspeed:

weight_decay: 0.0

fsdp:

fsdp_config:

special_tokens:



```

</details><br>

# Mistral-7B-wikipedia_ru_pruned-0.1_merged



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.

It achieves the following results on the evaluation set:

- Loss: 1.1876



## Training procedure



### Training hyperparameters



The following hyperparameters were used during training:

- learning_rate: 0.0002
- train_batch_size: 11
- eval_batch_size: 11
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10

- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5643        | 0.0   | 0    |                 |
| 1.012         | 1.0   | 1100 | 1.1876          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0