|
--- |
|
base_model: alpindale/Mistral-7B-v0.2-hf |
|
language: |
|
- en |
|
license: apache-2.0 |
|
datasets: |
|
- cognitivecomputations/dolphin |
|
- cognitivecomputations/dolphin-coder |
|
- cognitivecomputations/samantha-data |
|
- jondurbin/airoboros-2.2.1 |
|
- teknium/openhermes-2.5 |
|
- m-a-p/Code-Feedback |
|
- m-a-p/CodeFeedback-Filtered-Instruction |
|
model-index: |
|
- name: dolphin-2.8-mistral-7b-v02 |
|
results: |
|
- task: |
|
type: text-generation |
|
dataset: |
|
type: openai_humaneval |
|
name: HumanEval |
|
metrics: |
|
- name: pass@1 |
|
type: pass@1 |
|
value: 0.469 |
|
verified: false |
|
--- |
|
|
|
# Dolphin 2.8 Mistral 7b v0.2 🐬 |
|
|
|
By Eric Hartford and Cognitive Computations |
|
|
|
Discord: https://discord.gg/8fbBeC7ZGx |
|
|
|
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" /> |
|
|
|
My appreciation for the sponsors of Dolphin 2.8: |
|
- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 10xL40S node |
|
- [Winston Sou](https://twitter.com/WinsonDabbles) - Along with a generous anonymous sponsor, donated a massive personally owned compute resource! |
|
- [Abacus AI](https://abacus.ai/) - my employer and partner in many things. |
|
|
|
This model is based on [Mistral-7b-v0.2](https://huggingface.co/alpindale/Mistral-7B-v0.2-hf) a new base model released by MistralAI on March 23, 2024 but they have not yet published on HuggingFace. Thanks to @alpindale for converting / publishing. |
|
|
|
The base model has 32k context, and the full-weights fine-tune was with 16k sequence lengths. |
|
|
|
It took 3 days on 10x L40S provided by [Crusoe Cloud](https://crusoe.ai/) |
|
|
|
Dolphin-2.8 has a variety of instruction, conversational, and coding skills. |
|
|
|
Dolphin is uncensored. I have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant to any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly. |
|
|
|
Dolphin is licensed Apache 2.0. I grant permission for any use including commercial. Dolphin was trained on data generated from GPT4 among other models. |
|
|
|
# Evals |
|
|
|
``` |
|
{ |
|
"arc_challenge": { |
|
"acc,none": 0.5921501706484642, |
|
"acc_stderr,none": 0.014361097288449701, |
|
"acc_norm,none": 0.6339590443686007, |
|
"acc_norm_stderr,none": 0.014077223108470139 |
|
}, |
|
"gsm8k": { |
|
"exact_match,strict-match": 0.4783927217589083, |
|
"exact_match_stderr,strict-match": 0.013759618667051773, |
|
"exact_match,flexible-extract": 0.5367702805155421, |
|
"exact_match_stderr,flexible-extract": 0.013735191956468648 |
|
}, |
|
"hellaswag": { |
|
"acc,none": 0.6389165504879506, |
|
"acc_stderr,none": 0.004793330525656218, |
|
"acc_norm,none": 0.8338976299541924, |
|
"acc_norm_stderr,none": 0.00371411888431746 |
|
}, |
|
"mmlu": { |
|
"acc,none": 0.6122347243982339, |
|
"acc_stderr,none": 0.003893774654142997 |
|
}, |
|
"truthfulqa_mc2": { |
|
"acc,none": 0.5189872652778472, |
|
"acc_stderr,none": 0.014901128316426086 |
|
}, |
|
"winogrande": { |
|
"acc,none": 0.7971586424625099, |
|
"acc_stderr,none": 0.011301439925936643 |
|
} |
|
} |
|
``` |
|
|
|
[<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: alpindale/Mistral-7B-v0.2-hf |
|
model_type: MistralForCausalLM |
|
tokenizer_type: LlamaTokenizer |
|
is_mistral_derived_model: true |
|
|
|
load_in_8bit: false |
|
load_in_4bit: false |
|
strict: false |
|
|
|
datasets: |
|
- path: /workspace/datasets/dolphin201-sharegpt2.jsonl |
|
type: sharegpt |
|
- path: /workspace/datasets/dolphin-coder-translate-sharegpt2.jsonl |
|
type: sharegpt |
|
- path: /workspace/datasets/dolphin-coder-codegen-sharegpt2.jsonl |
|
type: sharegpt |
|
- path: /workspace/datasets/m-a-p_Code-Feedback-sharegpt.jsonl |
|
type: sharegpt |
|
- path: /workspace/datasets/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt.jsonl |
|
type: sharegpt |
|
- path: /workspace/datasets/not_samantha_norefusals.jsonl |
|
type: sharegpt |
|
- path: /workspace/datasets/openhermes2_5-sharegpt.jsonl |
|
type: sharegpt |
|
|
|
chat_template: chatml |
|
|
|
dataset_prepared_path: last_run_prepared |
|
val_set_size: 0.001 |
|
output_dir: /workspace/dolphin-2.8-mistral-7b |
|
|
|
sequence_len: 16384 |
|
sample_packing: true |
|
pad_to_sequence_len: true |
|
|
|
wandb_project: dolphin |
|
wandb_entity: |
|
wandb_watch: |
|
wandb_run_id: |
|
wandb_log_model: |
|
|
|
gradient_accumulation_steps: 8 |
|
micro_batch_size: 3 |
|
num_epochs: 4 |
|
adam_beta2: 0.95 |
|
adam_epsilon: 0.00001 |
|
max_grad_norm: 1.0 |
|
lr_scheduler: cosine |
|
learning_rate: 0.000005 |
|
optimizer: adamw_bnb_8bit |
|
|
|
train_on_inputs: false |
|
group_by_length: false |
|
bf16: true |
|
fp16: false |
|
tf32: false |
|
|
|
gradient_checkpointing: true |
|
gradient_checkpointing_kwargs: |
|
use_reentrant: true |
|
early_stopping_patience: |
|
resume_from_checkpoint: |
|
local_rank: |
|
logging_steps: 1 |
|
xformers_attention: |
|
flash_attention: true |
|
|
|
warmup_steps: 10 |
|
|
|
eval_steps: 73 |
|
eval_table_size: |
|
eval_table_max_new_tokens: |
|
eval_sample_packing: false |
|
saves_per_epoch: |
|
save_steps: 73 |
|
save_total_limit: 2 |
|
debug: |
|
deepspeed: deepspeed_configs/zero3_bf16.json |
|
weight_decay: 0.1 |
|
fsdp: |
|
fsdp_config: |
|
special_tokens: |
|
eos_token: "<|im_end|>" |
|
tokens: |
|
- "<|im_start|>" |
|
|
|
``` |
|
|
|
</details><br> |
|
|
|
# workspace/dolphin-2.8-mistral-7b |
|
|
|
This model is a fine-tuned version of [alpindale/Mistral-7B-v0.2-hf](https://huggingface.co/alpindale/Mistral-7B-v0.2-hf) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4828 |
|
|
|
## 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: 5e-06 |
|
- train_batch_size: 3 |
|
- eval_batch_size: 3 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 10 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 240 |
|
- total_eval_batch_size: 30 |
|
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 10 |
|
- num_epochs: 4 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 1.1736 | 0.0 | 1 | 1.0338 | |
|
| 0.6106 | 0.36 | 73 | 0.5439 | |
|
| 0.5766 | 0.72 | 146 | 0.5171 | |
|
| 0.5395 | 1.06 | 219 | 0.5045 | |
|
| 0.5218 | 1.42 | 292 | 0.4976 | |
|
| 0.5336 | 1.78 | 365 | 0.4915 | |
|
| 0.5018 | 2.13 | 438 | 0.4885 | |
|
| 0.5113 | 2.48 | 511 | 0.4856 | |
|
| 0.5066 | 2.84 | 584 | 0.4838 | |
|
| 0.4967 | 3.19 | 657 | 0.4834 | |
|
| 0.4956 | 3.55 | 730 | 0.4830 | |
|
| 0.5026 | 3.9 | 803 | 0.4828 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.0.dev0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.0 |
|
|
|
|
|
# Quants |
|
|
|
- [dagbs/-GGUF](https://huggingface.co/dagbs/dolphin-2.8-mistral-7b-v02-GGUF) |
|
|
|
- [bartowski/ExLlamaV2](https://huggingface.co/bartowski/dolphin-2.8-mistral-7b-v02-exl2) |
|
|
|
- [solidrust/AWQ](https://huggingface.co/solidrust/dolphin-2.8-mistral-7b-v02-AWQ) |
