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dolphin-2.9.1-qwen-110b

dphn / dolphin-2.9.1-qwen-110b

Run on huggingface.co
huggingface.co
Total runs: 36
24-hour runs: 1
7-day runs: -18
30-day runs: -23
Model's Last Updated: May 20 2024
text-generation

Introduction of dolphin-2.9.1-qwen-110b

Model Details of dolphin-2.9.1-qwen-110b

Dolphin 2.9.1 Qwen 110b 🐬

Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations

Discord Discord: https://discord.gg/cognitivecomputations

Our appreciation for the sponsors of Dolphin 2.9.1:

This model is based on Qwen1.5-110B, and is governed by tongyi-qianwen license

The base model has 32k context, and the full-weight fine-tuning was with 8k sequence length.

This model was trained FFT on parameters selected by Laser Scanner , using ChatML prompt template format.

example: 

<|im_start|>system
You are Dolphin, a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Dolphin-2.9.1 has a variety of instruction, conversational, and coding skills. It also has initial agentic abilities and supports function calling.

Dolphin is uncensored. We 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 with 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 according to Qwen's tongyi-qianwen license. We grant permission for any use, including commercial, that falls within accordance with said license. Dolphin was trained on data generated from GPT4, among other models.

Evals

image/png

Training

Built with Axolotl

See axolotl config

axolotl version: 0.4.0 

base_model: /workspace/axolotl/qwen-checkpoint
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

# trust_remote_code: true

# load_in_8bit: true
# load_in_4bit: true
# strict: false

datasets:
  - path: /workspace/datasets/dolphin-2.9/dolphin201-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  # - path: /workspace/datasets/dolphin-2.9/Ultrachat200kunfiltered.jsonl
  #   type: sharegpt
  #   conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/dolphin-coder-translate-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/dolphin-coder-codegen-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/not_samantha_norefusals.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/Orca-Math-resort-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/agent_instruct_react_unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_instruct_j1s1_3k_unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_negative_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_react_10p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_tflan_cot_30p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/openhermes200k_unfiltered.jsonl
    type: sharegpt 
    conversation: chatml
  # - path: /workspace/datasets/dolphin-2.9/SystemConversations.jsonl
  #   type: sharegpt
  #   conversation: chatml

chat_template: chatml
dataset_prepared_path: last_run_prepared
val_set_size: 0.01
output_dir: ./qwen-out

# adapter: qlora
# lora_r: 16
# lora_alpha: 16
# lora_modules_to_save: [embed_tokens, lm_head]
# lora_dropout: 0.05
# lora_target_linear: false

unfrozen_parameters:
- ^lm_head.weight$
- ^model.embed_tokens.weight$
# input_layernorm layers
- model.layers.0.input_layernorm
- model.layers.1.input_layernorm
- model.layers.2.input_layernorm
- model.layers.3.input_layernorm
- model.layers.4.input_layernorm
- model.layers.5.input_layernorm
- model.layers.6.input_layernorm
- model.layers.7.input_layernorm
- model.layers.8.input_layernorm
- model.layers.9.input_layernorm
- model.layers.10.input_layernorm
- model.layers.11.input_layernorm
- model.layers.12.input_layernorm
- model.layers.13.input_layernorm
- model.layers.14.input_layernorm
- model.layers.15.input_layernorm
- model.layers.16.input_layernorm
- model.layers.17.input_layernorm
- model.layers.18.input_layernorm
- model.layers.19.input_layernorm
- model.layers.20.input_layernorm
- model.layers.21.input_layernorm
- model.layers.22.input_layernorm
- model.layers.23.input_layernorm
# lm_head layers
# mlp.down_proj layers
- model.layers.17.mlp.down_proj
- model.layers.18.mlp.down_proj
- model.layers.19.mlp.down_proj
- model.layers.20.mlp.down_proj
- model.layers.21.mlp.down_proj
- model.layers.22.mlp.down_proj
- model.layers.23.mlp.down_proj
- model.layers.24.mlp.down_proj
- model.layers.25.mlp.down_proj
- model.layers.26.mlp.down_proj
- model.layers.27.mlp.down_proj
- model.layers.28.mlp.down_proj
- model.layers.29.mlp.down_proj
- model.layers.30.mlp.down_proj
- model.layers.31.mlp.down_proj
- model.layers.32.mlp.down_proj
- model.layers.33.mlp.down_proj
- model.layers.34.mlp.down_proj
- model.layers.35.mlp.down_proj
- model.layers.36.mlp.down_proj
- model.layers.37.mlp.down_proj
- model.layers.38.mlp.down_proj
- model.layers.39.mlp.down_proj
- model.layers.40.mlp.down_proj
# mlp.gate_proj layers
- model.layers.51.mlp.gate_proj
- model.layers.50.mlp.gate_proj
- model.layers.53.mlp.gate_proj
- model.layers.52.mlp.gate_proj
- model.layers.49.mlp.gate_proj
- model.layers.45.mlp.gate_proj
- model.layers.46.mlp.gate_proj
- model.layers.47.mlp.gate_proj
- model.layers.57.mlp.gate_proj
- model.layers.48.mlp.gate_proj
- model.layers.56.mlp.gate_proj
- model.layers.41.mlp.gate_proj
- model.layers.54.mlp.gate_proj
- model.layers.43.mlp.gate_proj
- model.layers.44.mlp.gate_proj
- model.layers.60.mlp.gate_proj
- model.layers.55.mlp.gate_proj
- model.layers.40.mlp.gate_proj
- model.layers.42.mlp.gate_proj
- model.layers.58.mlp.gate_proj
- model.layers.36.mlp.gate_proj
- model.layers.37.mlp.gate_proj
- model.layers.38.mlp.gate_proj
- model.layers.39.mlp.gate_proj
# mlp.up_proj layers
- model.layers.50.mlp.up_proj
- model.layers.51.mlp.up_proj
- model.layers.41.mlp.up_proj
- model.layers.49.mlp.up_proj
- model.layers.43.mlp.up_proj
- model.layers.44.mlp.up_proj
- model.layers.40.mlp.up_proj
- model.layers.45.mlp.up_proj
- model.layers.47.mlp.up_proj
- model.layers.48.mlp.up_proj
- model.layers.46.mlp.up_proj
- model.layers.42.mlp.up_proj
- model.layers.39.mlp.up_proj
- model.layers.36.mlp.up_proj
- model.layers.37.mlp.up_proj
- model.layers.38.mlp.up_proj
- model.layers.56.mlp.up_proj
- model.layers.57.mlp.up_proj
- model.layers.53.mlp.up_proj
- model.layers.31.mlp.up_proj
- model.layers.32.mlp.up_proj
- model.layers.34.mlp.up_proj
- model.layers.35.mlp.up_proj
- model.layers.33.mlp.up_proj
# model.embed_tokens layers
# model.norm layers
# post_attention_layernorm layers
- model.layers.0.post_attention_layernorm
- model.layers.1.post_attention_layernorm
- model.layers.2.post_attention_layernorm
- model.layers.3.post_attention_layernorm
- model.layers.4.post_attention_layernorm
- model.layers.5.post_attention_layernorm
- model.layers.6.post_attention_layernorm
- model.layers.7.post_attention_layernorm
- model.layers.8.post_attention_layernorm
- model.layers.9.post_attention_layernorm
- model.layers.10.post_attention_layernorm
- model.layers.11.post_attention_layernorm
- model.layers.12.post_attention_layernorm
- model.layers.13.post_attention_layernorm
- model.layers.14.post_attention_layernorm
- model.layers.15.post_attention_layernorm
- model.layers.16.post_attention_layernorm
- model.layers.17.post_attention_layernorm
- model.layers.18.post_attention_layernorm
- model.layers.19.post_attention_layernorm
- model.layers.20.post_attention_layernorm
- model.layers.21.post_attention_layernorm
- model.layers.22.post_attention_layernorm
- model.layers.23.post_attention_layernorm
# self_attn.k_proj layers
- model.layers.42.self_attn.k_proj
- model.layers.41.self_attn.k_proj
- model.layers.39.self_attn.k_proj
- model.layers.35.self_attn.k_proj
- model.layers.28.self_attn.k_proj
- model.layers.79.self_attn.k_proj
- model.layers.43.self_attn.k_proj
- model.layers.32.self_attn.k_proj
- model.layers.73.self_attn.k_proj
- model.layers.31.self_attn.k_proj
- model.layers.29.self_attn.k_proj
- model.layers.76.self_attn.k_proj
- model.layers.30.self_attn.k_proj
- model.layers.40.self_attn.k_proj
- model.layers.33.self_attn.k_proj
- model.layers.78.self_attn.k_proj
- model.layers.34.self_attn.k_proj
- model.layers.37.self_attn.k_proj
- model.layers.45.self_attn.k_proj
- model.layers.44.self_attn.k_proj
- model.layers.71.self_attn.k_proj
- model.layers.26.self_attn.k_proj
- model.layers.74.self_attn.k_proj
- model.layers.27.self_attn.k_proj
# self_attn.o_proj layers
- model.layers.35.self_attn.o_proj
- model.layers.34.self_attn.o_proj
- model.layers.37.self_attn.o_proj
- model.layers.33.self_attn.o_proj
- model.layers.31.self_attn.o_proj
- model.layers.27.self_attn.o_proj
- model.layers.38.self_attn.o_proj
- model.layers.24.self_attn.o_proj
- model.layers.39.self_attn.o_proj
- model.layers.43.self_attn.o_proj
- model.layers.29.self_attn.o_proj
- model.layers.0.self_attn.o_proj
- model.layers.50.self_attn.o_proj
- model.layers.32.self_attn.o_proj
- model.layers.45.self_attn.o_proj
- model.layers.30.self_attn.o_proj
- model.layers.60.self_attn.o_proj
- model.layers.23.self_attn.o_proj
- model.layers.18.self_attn.o_proj
- model.layers.67.self_attn.o_proj
- model.layers.57.self_attn.o_proj
- model.layers.20.self_attn.o_proj
- model.layers.76.self_attn.o_proj
- model.layers.28.self_attn.o_proj
# self_attn.q_proj layers
- model.layers.1.self_attn.q_proj
- model.layers.6.self_attn.q_proj
- model.layers.0.self_attn.q_proj
- model.layers.5.self_attn.q_proj
- model.layers.2.self_attn.q_proj
- model.layers.7.self_attn.q_proj
- model.layers.3.self_attn.q_proj
- model.layers.4.self_attn.q_proj
- model.layers.8.self_attn.q_proj
- model.layers.9.self_attn.q_proj
- model.layers.61.self_attn.q_proj
- model.layers.10.self_attn.q_proj
- model.layers.62.self_attn.q_proj
- model.layers.36.self_attn.q_proj
- model.layers.15.self_attn.q_proj
- model.layers.11.self_attn.q_proj
- model.layers.17.self_attn.q_proj
- model.layers.60.self_attn.q_proj
- model.layers.63.self_attn.q_proj
- model.layers.64.self_attn.q_proj
- model.layers.29.self_attn.q_proj
- model.layers.30.self_attn.q_proj
- model.layers.55.self_attn.q_proj
- model.layers.34.self_attn.q_proj
# self_attn.v_proj layers
- model.layers.12.self_attn.v_proj
- model.layers.16.self_attn.v_proj
- model.layers.18.self_attn.v_proj
- model.layers.19.self_attn.v_proj
- model.layers.20.self_attn.v_proj
- model.layers.21.self_attn.v_proj
- model.layers.22.self_attn.v_proj
- model.layers.23.self_attn.v_proj
- model.layers.24.self_attn.v_proj
- model.layers.25.self_attn.v_proj
- model.layers.26.self_attn.v_proj
- model.layers.27.self_attn.v_proj
- model.layers.28.self_attn.v_proj
- model.layers.29.self_attn.v_proj
- model.layers.30.self_attn.v_proj
- model.layers.31.self_attn.v_proj
- model.layers.32.self_attn.v_proj
- model.layers.33.self_attn.v_proj
- model.layers.34.self_attn.v_proj
- model.layers.35.self_attn.v_proj
- model.layers.36.self_attn.v_proj
- model.layers.37.self_attn.v_proj
- model.layers.38.self_attn.v_proj
- model.layers.39.self_attn.v_proj



sequence_len: 8192 # supports up to 8192
sample_packing: true
pad_to_sequence_len: true

# adapter: lora
# lora_model_dir:
# lora_r: 32
# lora_alpha: 16
# lora_dropout: 0.05
# lora_target_linear: true
# lora_fan_in_fan_out:

wandb_project: dolphin-2.9-qwen-1.5-110b
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_8bit
lr_scheduler: cosine
learning_rate: 1e-5

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true

gradient_checkpointing: true
early_stopping_patience:
# resume_from_checkpoint: /workspace/axolotl/qwen-checkpoint
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 4
save_total_limit: 2
debug:
deepspeed: deepspeed_configs/zero3_bf16_cpuoffload_params.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  eos_token: "<|im_end|>"

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • total_eval_batch_size: 8
  • 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
0.3528 0.0 1 0.3848
0.3687 0.25 291 0.3988
0.4156 0.5 582 0.3966
0.3826 0.75 873 0.3931
Framework versions
  • Transformers 4.40.0.dev0
  • Pytorch 2.2.2+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0

Runs of dphn dolphin-2.9.1-qwen-110b on huggingface.co

36
Total runs
1
24-hour runs
-1
3-day runs
-18
7-day runs
-23
30-day runs

More Information About dolphin-2.9.1-qwen-110b huggingface.co Model

More dolphin-2.9.1-qwen-110b license Visit here:

https://choosealicense.com/licenses/tongyi-qianwen

dolphin-2.9.1-qwen-110b huggingface.co

dolphin-2.9.1-qwen-110b huggingface.co is an AI model on huggingface.co that provides dolphin-2.9.1-qwen-110b's model effect (), which can be used instantly with this dphn dolphin-2.9.1-qwen-110b model. huggingface.co supports a free trial of the dolphin-2.9.1-qwen-110b model, and also provides paid use of the dolphin-2.9.1-qwen-110b. Support call dolphin-2.9.1-qwen-110b model through api, including Node.js, Python, http.

dolphin-2.9.1-qwen-110b huggingface.co Url

https://huggingface.co/dphn/dolphin-2.9.1-qwen-110b

dphn dolphin-2.9.1-qwen-110b online free

dolphin-2.9.1-qwen-110b huggingface.co is an online trial and call api platform, which integrates dolphin-2.9.1-qwen-110b's modeling effects, including api services, and provides a free online trial of dolphin-2.9.1-qwen-110b, you can try dolphin-2.9.1-qwen-110b online for free by clicking the link below.

dphn dolphin-2.9.1-qwen-110b online free url in huggingface.co:

https://huggingface.co/dphn/dolphin-2.9.1-qwen-110b

dolphin-2.9.1-qwen-110b install

dolphin-2.9.1-qwen-110b is an open source model from GitHub that offers a free installation service, and any user can find dolphin-2.9.1-qwen-110b on GitHub to install. At the same time, huggingface.co provides the effect of dolphin-2.9.1-qwen-110b install, users can directly use dolphin-2.9.1-qwen-110b installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

dolphin-2.9.1-qwen-110b install url in huggingface.co:

https://huggingface.co/dphn/dolphin-2.9.1-qwen-110b

Url of dolphin-2.9.1-qwen-110b

dolphin-2.9.1-qwen-110b huggingface.co Url

Provider of dolphin-2.9.1-qwen-110b huggingface.co

dphn
ORGANIZATIONS
huggingface.co

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