File size: 3,689 Bytes
3d95ab9 e3d3457 3d95ab9 e3d3457 3d95ab9 e3d3457 ccacc8f e3d3457 f3401de e3d3457 f3401de e3d3457 cd30882 e3d3457 91e3b3f e3d3457 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 |
---
base_model: mistralai/Mistral-7B-v0.1
tags:
- mistral
- instruct
- finetune
- chatml
- gpt4
- synthetic data
- distillation
model-index:
- name: Thestral-0.1
results: []
license: apache-2.0
language:
- en
---
# Thestral v0.1
Thestral is Mistral Fine-tune. The model is a QLoRA version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the [Open-Orca/SlimOrca](https://huggingface.co/datasets/Open-Orca/SlimOrca).
This model is finetuned using `1xH100` using [axolotl](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
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: Open-Orca/SlimOrca
type: sharegpt
dataset_prepared_path: last_run_prepared
val_set_size: 0.1
output_dir: ./qlora-out_2
adapter: qlora
lora_model_dir:
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
lora_r: 128
lora_alpha: 32
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: slim_orca
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
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: 1
xformers_attention:
flash_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
unk_token: "<unk>"
```
</details><br>
GPT-4All Benchmark Set
| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr|
|-------------|------:|------|------|--------|-----:|---|-----:|
|winogrande | 1|none |None |acc |0.7498|± |0.0122|
|piqa | 1|none |None |acc |0.8172|± |0.0090|
| | |none |None |acc_norm|0.8286|± |0.0088|
|openbookqa | 1|none |None |acc |0.3380|± |0.0212|
| | |none |None |acc_norm|0.4420|± |0.0222|
|hellaswag | 1|none |None |acc |0.6254|± |0.0048|
| | |none |None |acc_norm|0.8061|± |0.0039|
|boolq | 2|none |None |acc |0.8740|± |0.0058|
|arc_easy | 1|none |None |acc |0.8199|± |0.0079|
| | |none |None |acc_norm|0.7891|± |0.0084|
|arc_challenge| 1|none |None |acc |0.5145|± |0.0146|
| | |none |None |acc_norm|0.5461|± |0.0145|
**Average: 71.93**
# 🤖 Additional information about training
This model is fine-tuned for 1.0 epoch.
<details><summary>Loss graph</summary>
</details><br>
Thanks to [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) for making the repository we used to make this model.
[<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) |