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dolphin-2.9.1-mixtral-1x22b

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dolphin-2.9.1-mixtral-1x22b / README.md
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metadata
base_model: cognitivecomputations/mixtral-1x22b-base
tags:
  - generated_from_trainer
model-index:
  - name: 1x22b-out
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.4.0

base_model: cognitivecomputations/mixtral-1x22b-base
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/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

chat_template: chatml
dataset_prepared_path: yi34b-prepared
val_set_size: 0.01
output_dir: ./1x22b-out

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

# 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: 16384 
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-mixtral1x22b
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 3
optimizer: adamw_8bit
lr_scheduler: cosine
learning_rate: 1e-5

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

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint: /workspace/axolotl2/axolotl/1x22b-out/checkpoint-507
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: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
weight_decay: 0.01
fsdp:
fsdp_config:
special_tokens:
  eos_token: "<|im_end|>"
  bos_token: "<s>"
  # pad_token: "<unk>"
  unk_token: "<unk>"
tokens:
- "<|im_start|>"

1x22b-out

This model is a fine-tuned version of cognitivecomputations/mixtral-1x22b-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4572

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: 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: 3

Training results

Training Loss Epoch Step Validation Loss
0.9818 0.0015 1 0.9854
0.4783 0.2499 169 0.5042
0.464 0.4997 338 0.4755
0.4561 0.7496 507 0.4593
0.3981 0.9994 676 0.4553
0.3725 1.2378 845 0.4525
0.3624 1.4877 1014 0.4457
0.359 1.7376 1183 0.4393
0.375 1.9874 1352 0.4345
0.2899 2.2260 1521 0.4488
0.2848 2.4759 1690 0.4473
0.2935 2.7257 1859 0.4470
0.2065 2.9756 2028 0.4572

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1